GAO-07-680, Unemployment Insurance: More Guidance and Evaluation of Worker-Profiling Initiative Could Help Improve State Efforts


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entitled 'Unemployment Insurance: More Guidance and Evaluation of 
Worker-Profiling Initiative Could Help improve State Efforts' which was 
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Report to Congressional Requesters: 

United States Government Accountability Office: 

GAO: 

June 2007: 

Unemployment Insurance: 

More Guidance and Evaluation of Worker-Profiling Initiative Could Help 
Improve State Efforts: 

GAO-07-680: 

GAO Highlights: 

Highlights of GAO-07-680, a report to congressional requesters 

Why GAO Did This Study: 

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 Found: 

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. 

Figure: Profiling Techniques Used in the United States: 

[See PDF for Image] 

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

[End of figure] 

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. 

[Hyperlink, http://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. 

[End of section] 

Contents: 

Letter: 

Results in Brief: 

Background: 

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 Study States Did Not Take the In-Depth Approach Recommended by 
Labor to Ensure That Profiled Claimants Obtain Reemployment Services: 

Little Is Known about Program's Effectiveness because There Are No 
Current Studies and Labor's Data Are of Limited Usefulness: 

Conclusions: 

Recommendations for Executive Action: 

Agency Comments: 

Appendix I: Objectives, Scope, and Methodology: 

Appendix II: Average Percentage of Claimants Profiled, Referred to, and 
Completing Services for 2002-2006 and Average Claimant Outcomes for 
2002-2005, by State: 

Appendix III: Bibliography of Research Studies on the Worker-Profiling 
Initiative--Exhaustive List Identified from the Literature Review: 

Appendix IV: Summary of the Impact of Referral to Services on Claimant 
Outcomes from the Literature Review: 

Appendix V: Comments from the Department of Labor: 

Appendix VI: GAO Contacts and Acknowledgments: 

Related GAO Products: 

Tables: 

Table 1: Labor-Recommended Factors: 

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

Table 3: Research Studies Included in Our Literature Review: 

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

Table 5: National Averages and Ranges of State Averages on Outcomes for 
Claimants Profiled and Referred to Services, 2002 to 2005: 

Figures: 

Figure 1: Process for Profiling, Referring, and Providing Reemployment 
Services to Claimants: 

Figure 2: Profiling Techniques Used in the States: 

Figure 3: States' Adjustments of Model Coefficients: 

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

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

Figure 6: Percentage of Claimants Completing Services, of Those 
Profiled: 

Abbreviations: 

ETA: Employment and Training Administration: 

UI: Unemployment Insurance: 

WIA: Workforce Investment Act: 

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 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. 

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: 

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 these questions, we used a combination of national data, in- 
depth 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. 

Results in Brief: 

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 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 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. 

Background: 

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 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.[Footnote 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.[Footnote 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.[Footnote 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 recommended also considering some additional factors 
such as claimants' education, tenure at previous job, and the state 
unemployment rate.[Footnote 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. 

Figure 1: Process for Profiling, Referring, and Providing Reemployment 
Services to Claimants: 

[See PDF for image] 

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. 

[End of figure] 

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 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.[Footnote 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.[Footnote 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.[Footnote 7] From 2001 to 2005, Labor also provided 
Reemployment Services grants to all states in order to enhance and 
target services to claimants through the nation's network of one-stop 
employment service centers.[Footnote 8] 

Most States Use Statistical Models to Identify Claimants Likely to 
Exhaust Benefits, but Many Have Not Updated Them to Account for 
Changing Economic Conditions: 

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. 

Most States Use Statistical Models instead of More Limited 
Characteristic Screens: 

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.[Footnote 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.[Footnote 10] 

Table 1: Labor-Recommended Factors: 

Factor[A]: Education; 
Impact on unemployment: Claimants with less education are more likely 
to exhaust benefits. 

Factor[A]: Job tenure; 
Impact on unemployment: Claimants with long attachment to a specific 
employer have more difficulty in finding equivalent employment 
elsewhere. 

Factor[A]: Industry[A]; 
Impact on unemployment: 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. 

Factor[A]: Occupation[A]; 
Impact on unemployment: Workers in low demand occupations experience 
greater reemployment difficulty than workers in occupations with high 
demand. 

Factor[A]: Unemployment rate; 
Impact on unemployment: 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. 

[End of table] 

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 
Employment Research,[Footnote 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.[Footnote 
12] 

Figure 2: Profiling Techniques Used in the States: 

[See PDF for image] 

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

[End of figure] 

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 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.[Footnote 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. 

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. 

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

Variable category: Delay in filing of claim; 
State: Calif.: [Empty]; 
State: Ill.: Check; 
State: Ky.: [Empty]; 
State: Tex.: Check; 
State: Wash.: [Empty]; 
Increased likelihood of exhaustion: Claimants who delay filing claims, 
indicating an unsuccessful job search. 

Variable category: Potential duration; 
State: Calif.: [Empty]; 
State: Ill.: [Empty]; 
State: Ky.: [Empty]; 
State: Tex.: Check; 
State: Wash.: Check; 
Increased likelihood of exhaustion: Claimants with short duration of 
eligibility for benefits. 

Variable category: Exhaustion rate by sub-state region; 
State: Calif.: Check; 
State: Ill.: [Empty]; 
State: Ky.: [Empty]; 
State: Tex.: [Empty]; 
State: Wash.: [Empty]; 
Increased likelihood of exhaustion: Claimants who live in areas of the 
state that have a high rate of exhaustion. 

Variable category: Past wages (base period wages); 
State: Calif.: [Empty]; 
State: Ill.: Check; 
State: Ky.: Check; 
State: Tex.: [Empty]; 
State: Wash.: [Empty]; 
Increased likelihood of exhaustion: Claimants with higher past wages. 

Variable category: Prior UI recipient; 
State: Calif.: [Empty]; 
State: Ill.: [Empty]; 
State: Ky.: Check; 
State: Tex.: [Empty]; 
State: Wash.: [Empty]; 
Increased likelihood of exhaustion: Claimants who have prior UI claims. 

Variable category: Reason for unemployment; 
State: Calif.: [Empty]; 
State: Ill.: Check; 
State: Ky.: [Empty]; 
State: Tex.: [Empty]; 
State: Wash.: [Empty]; 
Increased likelihood of exhaustion: Claimants who have been discharged 
from work for reasons other than being laid off. 

Variable category: Number of recent employers; 
State: Calif.: [Empty]; 
State: Ill.: Check; 
State: Ky.: [Empty]; 
State: Tex.: [Empty]; 
State: Wash.: [Empty]; 
Increased likelihood of exhaustion: Claimants with more than one 
employer. 

Variable category: Employer's history of layoffs[A]; 
State: Calif.: [Empty]; 
State: Ill.: [Empty];
State: Ky.: [Empty]; 
State: Tex.: [Empty]; 
State: Wash.: Check; 
Increased likelihood of exhaustion: 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. 

[End of table] 

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 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,[Footnote 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 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.[Footnote 15] A recent Labor-commissioned survey revealed that 
many states have not updated their profiling models in recent 
years.[Footnote 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: 

[See PDF for image] 

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

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

[End of figure] 

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: 

[See PDF for image] 

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

Note: No states adjusted models between 1997 and 1999. 

[End of figure] 

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 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. 

Most Study States Did Not Take the In-Depth Approach Recommended by 
Labor to Ensure That Profiled Claimants Obtain Reemployment Services: 

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. 

Data Collected by Labor Provided a Limited Picture of States' 
Implementation of Reemployment Services: 

Between 2002 and 2006, about 94 percent of the UI claimants who 
received a first payment were profiled.[Footnote 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.)[Footnote 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. 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: 

[See PDF for image] 

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

[End of figure] 

Figure 6: Percentage of Claimants Completing Services, of Those 
Profiled: 

[See PDF for image] 

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

[End of figure] 

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 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.[Footnote 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.[Footnote 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 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. 

Little Is Known about Program's Effectiveness because There Are No 
Current Studies and Labor's Data Are of Limited Usefulness: 

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.[Footnote 21] In addition, state officials said they do not 
use Labor's data for evaluation purposes. 

Early Research Showed Some Positive Outcomes for Those Referred to 
Services, but There Are No Current Studies: 

Five methodologically sound studies looking at the impacts of the 
worker-profiling 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.[Footnote 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.[Footnote 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 reemployment services provided 
then may not reflect what states are currently offering.[Footnote 24] 

Table 3: Research Studies Included in Our Literature Review: 

Kentucky studies. 

Research study: Black and others 2003; 
Data: states and time frame[A]: Kentucky, 1994-1996. 

Research study: Black and others 2007; 
Data: states and time frame[A]: Kentucky, 1994-1996. 

Research study: Noel 1998[B]; 
Data: states and time frame[A]: Kentucky, 1994-1996. 

Multistate studies. 

Research study: Dickinson and others 1997; 
Data: states and time frame[A]: Delaware[C] , Kentucky, New Jersey, 
1994-1995. 

Research study: Dickinson and others 1999; 
Data: states and time frame[A]: 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. 

[End of table] 

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.)[Footnote 25] According to the studies, claimants who were 
referred to services had a decreased UI duration and received lower 
total amounts of UI benefits.[Footnote 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 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: Duration of UI receipt; 
Range of effect found in research studies: Reduced by 0.2 to 4 weeks. 

Claimant outcome: Amount of UI benefits received; 
Range of effect found in research studies: Reduced by $55 to $320. 

Claimant outcome: Lessened likelihood of UI benefit exhaustion; 
Range of effect found in research studies: Inconclusive. 

Claimant outcome: Earnings following UI claim; 
Range of effect found in research studies: Increased by $218 to 
$1,054[A]. 

Claimant outcome: Employment rates following UI claim; 
Range of effect found in research studies: 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. 

[End of table] 

Research studies of other work search programs corroborate the 
generally favorable results found in the impact evaluation studies of 
the worker-profiling initiative.[Footnote 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 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 data[Footnote 28] were 
sufficiently reliable for us to report only certain outcomes, including 
benefits exhaustion, weeks of benefit receipt, and 
reemployment.[Footnote 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). 

Table 5: National Averages and Ranges of State Averages on Outcomes for 
Claimants Profiled and Referred to Services, 2002 to 2005: 

Claimant outcome: Claimants who exhausted their UI benefits; 
National average: 40 percent; 
Range of state averages[A]: 13 percent to 60 percent. 

Claimant outcome: Number of weeks that claimants received UI 
benefits[B]; 
National average: 17 weeks; 
Range of state averages[A]: 7 to 27 weeks. 

Claimant outcome: Claimants who found employment at some point during 
the year subsequent to the referral to services; 
National average: 53 percent; 
Range of state averages[A]: 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. 

[End of table] 

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.[Footnote 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.[Footnote 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 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.[Footnote 32] 

Conclusions: 

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. 

A long time has passed since Labor articulated its vision of 
reemployment services, and our review of seven states indicates that 
what is being 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. 

Recommendations for Executive Action: 

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: 

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. 

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. 

Agency Comments: 

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. 

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. 

Signed by: 

Sigurd R. Nilsen: 
Director, Education, Workforce, and Income Security Issues: 

[End of section] 

Appendix I: Objectives, Scope, and 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.[Footnote 33] 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 report, 
states submit to Labor, by quarter, information such as the number of 
UI claimants profiled, referred to services, and completing 
services.[Footnote 34] 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.[Footnote 35] 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.[Footnote 36] In this report, 
states report to Labor on a quarterly basis information on the outcomes 
of referred claimants, such as the average 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.[Footnote 37] 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. 

* 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. 

[End of section] 

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: Ala; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 102%; 
Profiled claimants referred to services (2002-2006): 3%; 
Profiled claimants who completed services (2002-2006): 3%; 
Referred claimants who exhaust UI benefits (2002-2005): 47%; 
Referred claimants who become employed (2002-2005): 56%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 18.3. 

State: Alaska; Claimants receiving first UI benefit payment who were 
profiled (2002-2006): 89%; 
Profiled claimants referred to services (2002-2006): 8%; 
Profiled claimants who completed services (2002-2006): 5%; 
Referred claimants who exhaust UI benefits (2002-2005): 42%; 
Referred claimants who become employed (2002-2005): 60%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 14.2. 

State: Ariz; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 86%; 
Profiled claimants referred to services (2002-2006): 16%; 
Profiled claimants who completed services (2002- 2006): 9%; 
Referred claimants who exhaust UI benefits (2002-2005): 37%; 
Referred claimants who become employed (2002-2005): 51%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 14.6. 

State: Ark; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 95%; 
Profiled claimants referred to services (2002-2006): 2%; 
Profiled claimants who completed services (2002-2006): 1%; 
Referred claimants who exhaust UI benefits (2002-2005): 46%; 
Referred claimants who become employed (2002-2005): 38%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 21.0. 

State: Calif; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 59%; 
Profiled claimants referred to services (2002-2006): 14%; 
Profiled claimants who completed services (2002- 2006): 7%; 
Referred claimants who exhaust UI benefits (2002-2005): 32%; 
Referred claimants who become employed (2002-2005): Not available; 
Length of time referred claimants receive UI benefits (weeks) (2002- 
2005): 21.3. 

State: Colo; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 100%; 
Profiled claimants referred to services (2002-2006): 2%; 
Profiled claimants who completed services (2002-2006): 1%; 
Referred claimants who exhaust UI benefits (2002-2005): 45%; 
Referred claimants who become employed (2002-2005): 58%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 16.3. 

State: Conn; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 82%; 
Profiled claimants referred to services (2002-2006): 13%; 
Profiled claimants who completed services (2002- 2006): 8%; 
Referred claimants who exhaust UI benefits (2002-2005): 47%; 
Referred claimants who become employed (2002-2005): 58%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 17.7. 

State: Del; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 162%; 
Profiled claimants referred to services (2002-2006): 4%; 
Profiled claimants who completed services (2002-2006): 3%; 
Referred claimants who exhaust UI benefits (2002-2005): 58%; 
Referred claimants who become employed (2002-2005): 87%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 20.6. 

State: D.C; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 93%; 
Profiled claimants referred to services (2002-2006): 6%; 
Profiled claimants who completed services (2002-2006): 4%; 
Referred claimants who exhaust UI benefits (2002-2005): 57%; 
Referred claimants who become employed (2002-2005): 52%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 20.7. 

State: Fla; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 90%; 
Profiled claimants referred to services (2002-2006): 36%; 
Profiled claimants who completed services (2002- 2006): 21%; 
Referred claimants who exhaust UI benefits (2002-2005): 29%; 
Referred claimants who become employed (2002-2005): 29%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 27.0. 

State: Ga; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 74%; 
Profiled claimants referred to services (2002-2006): 25%; 
Profiled claimants who completed services (2002- 2006): 24%; 
Referred claimants who exhaust UI benefits (2002-2005): 49%; 
Referred claimants who become employed (2002-2005): Not available; 
Length of time referred claimants receive UI benefits (weeks) (2002- 
2005): 15.6. 

State: Hawaii; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 94%; 
Profiled claimants referred to services (2002-2006): 11%; 
Profiled claimants who completed services (2002- 2006): 7%; 
Referred claimants who exhaust UI benefits (2002-2005): 40%; 
Referred claimants who become employed (2002-2005): 60%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 18.2. 

State: Idaho; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 114%; 
Profiled claimants referred to services (2002-2006): 2%; 
Profiled claimants who completed services (2002-2006): 1%; 
Referred claimants who exhaust UI benefits (2002-2005): Not available; 
Referred claimants who become employed (2002-2005): Not available; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): Not available. 

State: Ind; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 97%; 
Profiled claimants referred to services (2002-2006): 8%; 
Profiled claimants who completed services (2002-2006): 5%; 
Referred claimants who exhaust UI benefits (2002-2005): 57%; 
Referred claimants who become employed (2002-2005): 61%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 13.3. 

State: Iowa; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 37%; 
Profiled claimants referred to services (2002-2006): 21%; 
Profiled claimants who completed services (2002- 2006): 13%; 
Referred claimants who exhaust UI benefits (2002-2005): 39%; 
Referred claimants who become employed (2002-2005): 58%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 18.9. 

State: Kan; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 71%; 
Profiled claimants referred to services (2002-2006): 6%; 
Profiled claimants who completed services (2002-2006): 6%; 
Referred claimants who exhaust UI benefits (2002-2005): 60%; 
Referred claimants who become employed (2002-2005): 52%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 12.8. 

State: Ky; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 136%; 
Profiled claimants referred to services (2002-2006): 13%; 
Profiled claimants who completed services (2002- 2006): 10%; 
Referred claimants who exhaust UI benefits (2002-2005): 43%; 
Referred claimants who become employed (2002-2005): 50%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 18.1. 

State: Maine; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 100%; 
Profiled claimants referred to services (2002-2006): 18%; 
Profiled claimants who completed services (2002- 2006): 11%; 
Referred claimants who exhaust UI benefits (2002-2005): 40%; 
Referred claimants who become employed (2002-2005): 64%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 15.1. 

State: Md; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 100%; 
Profiled claimants referred to services (2002-2006): 24%; 
Profiled claimants who completed services (2002- 2006): 12%; 
Referred claimants who exhaust UI benefits (2002-2005): 51%; 
Referred claimants who become employed (2002-2005): 43%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 20.9. 

State: Mass; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 100%; 
Profiled claimants referred to services (2002-2006): 26%; 
Profiled claimants who completed services (2002- 2006): 20%; 
Referred claimants who exhaust UI benefits (2002-2005): 53%; 
Referred claimants who become employed (2002-2005): 48%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 20.2. 

State: Mich; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 95%; 
Profiled claimants referred to services (2002-2006): 2%; 
Profiled claimants who completed services (2002-2006): 1%; 
Referred claimants who exhaust UI benefits (2002-2005): 36%; 
Referred claimants who become employed (2002-2005): 55%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 17.0. 

State: Minn; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 114%; 
Profiled claimants referred to services (2002-2006): 21%; 
Profiled claimants who completed services (2002- 2006): 19%; 
Referred claimants who exhaust UI benefits (2002-2005): 39%; 
Referred claimants who become employed (2002-2005): 59%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 17.5. 

State: Miss; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 115%; 
Profiled claimants referred to services (2002-2006): 22%; 
Profiled claimants who completed services (2002- 2006): 13%; 
Referred claimants who exhaust UI benefits (2002-2005): 44%; 
Referred claimants who become employed (2002-2005): 59%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 16.0. 

State: Mo; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 73%; 
Profiled claimants referred to services (2002-2006): 8%; 
Profiled claimants who completed services (2002-2006): 6%; 
Referred claimants who exhaust UI benefits (2002-2005): 51%; 
Referred claimants who become employed (2002-2005): 56%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 16.6. 

State: Mont; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 171%; 
Profiled claimants referred to services (2002-2006): 4%; 
Profiled claimants who completed services (2002-2006): 3%; 
Referred claimants who exhaust UI benefits (2002-2005): 53%; 
Referred claimants who become employed (2002-2005): 64%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 7.4. 

State: Neb; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 22%; 
Profiled claimants referred to services (2002-2006): 28%; 
Profiled claimants who completed services (2002- 2006): 24%; 
Referred claimants who exhaust UI benefits (2002-2005): 31%; 
Referred claimants who become employed (2002-2005): 85%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 16.1. 

State: Nev; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 96%; 
Profiled claimants referred to services (2002-2006): 4%; 
Profiled claimants who completed services (2002-2006): 3%; 
Referred claimants who exhaust UI benefits (2002-2005): 31%; 
Referred claimants who become employed (2002-2005): 46%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 7.3. 

State: N.H; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 112%; 
Profiled claimants referred to services (2002-2006): 26%; 
Profiled claimants who completed services (2002- 2006): 26%; 
Referred claimants who exhaust UI benefits (2002-2005): 13%; 
Referred claimants who become employed (2002-2005): 74%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 15.7. 

State: N.J; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 86%; 
Profiled claimants referred to services (2002-2006): 14%; 
Profiled claimants who completed services (2002- 2006): 14%; 
Referred claimants who exhaust UI benefits (2002-2005): Not available; 
Referred claimants who become employed (2002-2005): Not available; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): Not available. 

State: N.Y; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 93%; 
Profiled claimants referred to services (2002-2006): 12%; 
Profiled claimants who completed services (2002- 2006): 11%; 
Referred claimants who exhaust UI benefits (2002-2005): 60%; 
Referred claimants who become employed (2002-2005): 52%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 20.9. 

State: N.C; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 37%; 
Profiled claimants referred to services (2002-2006): 12%; 
Profiled claimants who completed services (2002- 2006): 7%; 
Referred claimants who exhaust UI benefits (2002-2005): 18%; 
Referred claimants who become employed (2002-2005): 22%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 20.1. 

State: N.D; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 123%; 
Profiled claimants referred to services (2002-2006): 20%; 
Profiled claimants who completed services (2002- 2006): 15%; 
Referred claimants who exhaust UI benefits (2002-2005): 18%; 
Referred claimants who become employed (2002-2005): 70%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 7.8. 

State: Ohio; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 94%; 
Profiled claimants referred to services (2002-2006): 13%; 
Profiled claimants who completed services (2002- 2006): 7%; 
Referred claimants who exhaust UI benefits (2002-2005): 21%; 
Referred claimants who become employed (2002-2005): 62%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 21.0. 

State: Okla; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 115%; 
Profiled claimants referred to services (2002-2006): 27%; 
Profiled claimants who completed services (2002- 2006): 23%; 
Referred claimants who exhaust UI benefits (2002-2005): 48%; 
Referred claimants who become employed (2002-2005): 51%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 18.5. 

State: Ore; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 74%; 
Profiled claimants referred to services (2002-2006): 13%; 
Profiled claimants who completed services (2002- 2006): 9%; 
Referred claimants who exhaust UI benefits (2002-2005): 42%; 
Referred claimants who become employed (2002-2005): 45%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 24.0. 

State: Pa; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 96%; 
Profiled claimants referred to services (2002-2006): 15%; 
Profiled claimants who completed services (2002- 2006): 10%; 
Referred claimants who exhaust UI benefits (2002-2005): 30%; 
Referred claimants who become employed (2002-2005): 28%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 22.7. 

State: R.I; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 74%; 
Profiled claimants referred to services (2002-2006): 20%; 
Profiled claimants who completed services (2002- 2006): 18%; 
Referred claimants who exhaust UI benefits (2002-2005): 48%; 
Referred claimants who become employed (2002-2005): 43%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 18.0. 

State: S.C; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 73%; 
Profiled claimants referred to services (2002-2006): 21%; 
Profiled claimants who completed services (2002- 2006): 14%; 
Referred claimants who exhaust UI benefits (2002-2005): 37%; 
Referred claimants who become employed (2002-2005): 52%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 10.2. 

State: S.D; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 86%; 
Profiled claimants referred to services (2002-2006): 7%; 
Profiled claimants who completed services (2002-2006): 6%; 
Referred claimants who exhaust UI benefits (2002-2005): 26%; 
Referred claimants who become employed (2002-2005): 55%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 13.8. 

State: Tenn; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 80%; 
Profiled claimants referred to services (2002-2006): 10%; 
Profiled claimants who completed services (2002- 2006): 8%; 
Referred claimants who exhaust UI benefits (2002-2005): 35%; 
Referred claimants who become employed (2002-2005): 40%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 21.2. 

State: Tex; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 89%; 
Profiled claimants referred to services (2002-2006): 49%; 
Profiled claimants who completed services (2002- 2006): 39%; 
Referred claimants who exhaust UI benefits (2002-2005): 39%; 
Referred claimants who become employed (2002-2005): 39%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 17.8. 

State: Utah; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 94%; 
Profiled claimants referred to services (2002-2006): 26%; 
Profiled claimants who completed services (2002- 2006): 24%; 
Referred claimants who exhaust UI benefits (2002-2005): 45%; 
Referred claimants who become employed (2002-2005): 38%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 15.0. 

State: Vt; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 99%; 
Profiled claimants referred to services (2002-2006): 7%; 
Profiled claimants who completed services (2002-2006): 5%; 
Referred claimants who exhaust UI benefits (2002-2005): 22%; 
Referred claimants who become employed (2002-2005): 48%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 17.2. 

State: Va; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 55%; 
Profiled claimants referred to services (2002-2006): 12%; 
Profiled claimants who completed services (2002- 2006): 7%; 
Referred claimants who exhaust UI benefits (2002-2005): 31%; 
Referred claimants who become employed (2002-2005): 31%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 24.2. 

State: Wash; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 116%; 
Profiled claimants referred to services (2002-2006): 52%; 
Profiled claimants who completed services (2002- 2006): 38%; 
Referred claimants who exhaust UI benefits (2002-2005): 26%; 
Referred claimants who become employed (2002-2005): 65%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 14.8. 

State: W.Va; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 122%; 
Profiled claimants referred to services (2002-2006): 21%; 
Profiled claimants who completed services (2002- 2006): 18%; 
Referred claimants who exhaust UI benefits (2002-2005): 45%; 
Referred claimants who become employed (2002-2005): 54%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 19.7. 

State: Wis; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 104%; 
Profiled claimants referred to services (2002-2006): 8%; 
Profiled claimants who completed services (2002-2006): 7%; 
Referred claimants who exhaust UI benefits (2002-2005): 44%; 
Referred claimants who become employed (2002-2005): 55%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 16.7. 

State: Wyo; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 115%; Profiled claimants referred to services (2002-2006): 1%; 
Profiled claimants who completed services (2002-2006): 1%; 
Referred claimants who exhaust UI benefits (2002-2005): 43%; 
Referred claimants who become employed (2002-2005): 47%; 
Length of time referred claimants receive UI benefits (weeks) (2002-
2005): 15.4. 

State: National Average; 
Claimants receiving first UI benefit payment who were profiled (2002-
2006): 94%; 
Profiled claimants referred to services (2002-2006): 15%; 
Profiled claimants who completed services (2002-2006): 11%; 
Referred claimants who exhaust UI benefits (2002- 2005): 40%; 
Referred claimants who become employed (2002-2005): 53%; 
Length of time referred claimants receive UI benefits (weeks) (2002- 
2005): 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. 

[End of table] 

[End of section] 

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). 

[End of section] 

Appendix IV: Summary of the Impact of Referral to Services on Claimant 
Outcomes from the Literature Review: 

Kentucky studies. 

Research study: Black and others 2003; 
Data[A]: Kentucky studies: KY, 1994-1996; 
Duration of UI receipt: Reduced by 2.2 weeks; 
Amount of UI benefits: Reduced by $143[C]; 
Benefit exhaustion rate: Not significant; 
Earnings following UI claim[B]: Increased by $1,054 in the year 
following UI claim; 
Employment rate following UI claim: Not available. 

Research study: Black and others 2007; 
Data[A]: Kentucky studies: KY, 1994-1996; 
Duration of UI receipt: Reduced by 0.4 to 2.3 weeks; 
Amount of UI benefits: Inconsistent results[D]; 
Benefit exhaustion rate: Not available; 
Earnings following UI claim[B]: Increased by $648 to $1,054 in the year 
following UI claim; 
Employment rate following UI claim: Not available. 

Research study: Noel 1998[E]; 
Data[A]: Kentucky studies: KY, 1994-1996; 
Duration of UI receipt: Reduced by 2.2 to 4 weeks; 
Amount of UI benefits: Reduced by $65 to $320; 
Benefit exhaustion rate: Not available; 
Earnings following UI claim[B]: Increased by $218 to $1,054 in the year 
following UI claim; 
Employment rate following UI claim: Not available. 

Multi-state studies. 

Research study: Dickinson and others 1997; 
Data[A]: Kentucky studies: DE[F] , KY, NJ,; 
1994-1995; 
Duration of UI receipt: KY, NJ: Reduced by 0.6 to 0.7 weeks; 
Amount of UI benefits: KY, NJ: Reduced by $96 to $109; 
Benefit exhaustion rate: NJ: Reduced by 4 percentage points; 
Earnings following UI claim[B]: NJ: Increased by $190 and $226 in the 
first and second quarters, respectively; 
Employment rate following UI claim: NJ: Increased by 1 percentage 
point[C] in first quarter. 

Research study: Dickinson and others 1999; 
Data[A]: Kentucky studies: CT, IL, KY, ME, NJ, SC, 1995-1996; 
Duration of UI receipt: CT, IL, KY, ME, NJ: Reduced by 0.2[C] to 1 
week; 
Amount of UI benefits: CT, IL, ME, NJ: Reduced by $55[C] to $139; 
Benefit exhaustion rate: CT, ME, NJ: Reduced by 1.4 to 4.3 percentage 
points SC, KY: Increased by 1.1[C] to 4.1 percentage points; 
Earnings following UI claim[B]: Inconsistent results; 
Employment rate following UI claim: 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. 

[End of table] 

[End of section] 

Appendix : Comments from the Department of Labor: 

U.S. Department of Labor: 
Assistant Secretary for Employment and Training: 
Washington, D.C. 20210: 

May 31 2007: 

Mr. Sigurd R. Nilsen: 
Director: 
Education, Workforce and Income Security Issues: 
U.S. Government Accountability Office: 
441 G Street, NW: 
Washington, DC 20548: 

Dear Mr. Nilsen: 

We appreciate the opportunity to review and comment on the draft 
report, "More Guidance and Evaluation of Worker-Profiling Initiative 
Could Help Improve State Efforts," GAO-07-680. In general, the U.S. 
Department of Labor agrees with the Government Accountability Office's 
(GAO) findings and has efforts already underway that are consistent 
with the report's recommendations. Our specific comments and 
observations are described below. 

As the result of a three-year research project sponsored by the 
Department to examine state profiling models and associated practices 
completed in March 2007, the Department shares some of the concerns 
raised by the GAO study and is reviewing ways to address these 
concerns. The amount of time that has elapsed since many states 
evaluated and updated their profiling models is a key concern. To call 
this issue to the attention of states, the Department will share recent 
findings and best practices from our research on profiling models as 
well as GAO's findings. In addition, the Department is developing 
training for state staff in evaluation of profiling data and will 
market its technical assistance in profiling model use/improvement more 
aggressively to states. 

The Department of Labor agrees with the need for continued focus on 
reemployment services for profiled claimants and is developing 
appropriate guidance and technical assistance to support states and 
local workforce investment areas in implementing effective reemployment 
service strategies. The Department intends to provide updated policy 
direction to states and local workforce areas on the requirement to 
maintain an effective Worker Profiling and Reemployment Services (WPRS) 
system and provide suggestions for promoting the integration of 
unemployment insurance (UI) and reemployment services for purposes of 
improving WPRS systems. The Employment and Training Administration 
(ETA) is sponsoring a regional conference for state and local workforce 
professionals in June 2007, Making the Connection: New Strategies for 
Reemploying Unemployment Insurance Claimants in the New Global Economy, 
which will feature effective reemployment strategies, strategies 
designed to better connect unemployment insurance claimants with the 
One-Stop Career Center system, use of local employment data to assist 
job seekers with finding in-demand jobs, and use of assessment tools. 
This conference is the first in a series of efforts focused on 
connecting unemployment insurance claimants with the One-Stop Career 
Center system. 

As discussed in the report, strategic use of assessments with profiled 
claimants, and in the workforce system broadly, can set the stage for 
effective employment and workforce preparation interventions. The 
Department will be issuing separate guidance to the workforce system on 
different types of assessments, criteria for their strategic use, and 
recommendations about the suite of tools that should be available 
through the One-Stop delivery system. This guidance will be followed by 
technical assistance via Webinars. 

GAO noted that the data collected by the Department related to 
profiling was originally intended as a starting point for states to 
assess their profiling programs and that the data collected is serving 
neither the states nor the federal government well. The Department will 
continue to work with the states to improve the accuracy of the 
existing reports, develop a plan to reassess the reports, and take 
steps to make the data useful to all parties. The Department will also 
consider, if resources permit, an evaluation of the impact of the 
worker-profiling initiative. 

Thank you for the opportunity to comment on this report. If you have 
any questions, please don't hesitate to call me at (202) 693-2700. 

Sincerely, 

Signed by: 

Emily Stover DeRocco: 

[End of section] 

Appendix VI: GAO Contacts and Acknowledgments: 

GAO Contact: 

Sigurd Nilsen, Director, (202) 512-7215 or nilsens@gao.gov: 

Staff Acknowledgments: 

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. 

[End of section] 

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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, 
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Workforce Investment Act: One-Stop Centers Implemented Strategies to 
Strengthen Services and Partnerships, but More Research and Information 
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FOOTNOTES 

[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). 

[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. 

[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, quasi-experimental 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. 

[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. 

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

[11] The 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. 

[12] Programs 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. 

[13] Marisa L. Kelso, "Worker Profiling and Reemployment Services 
Profiling Methods: Lessons Learned," U.S. Department of Labor, 
Unemployment Insurance Occasional Paper 99-5, June 1998. 

[14] Specifically, 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. 

[15] The Unemployment Compensation Amendments of 1993 (Pub. L. No. 103- 
152) do not require this type of monitoring of state performance. 

[16] In 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. 

[17] The 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. 

[18] Labor 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. 

[19] At 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. 

[20] U.S. Department of Labor, Employment and Training Administration, 
Field Memorandum No. 35-94, March 1994. 

[21] The 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. 

[22] These 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. 

[23] Texas, 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. 

[24] The reemployment services received by claimants in these studies 
typically included an orientation and then on average between one and 
two additional services after orientation. 

[25] See appendix IV for more detailed information on the claimant 
outcome effects broken out by research study. 

[26] 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. The amount of UI benefits received varies 
depending on a claimant's previous employment earnings and state UI 
laws. 

[27] The 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. 

[28] Labor collects claimant outcomes data from the states on Form ETA 
9049, Worker Profiling and Reemployment Services Outcomes. 

[29] Three 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. 

[30] Data 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. 

[31] Labor 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. 

[32] These performance indicators are for all UI claimants, not just 
the claimants that are profiled and referred to services under the 
worker-profiling program. 

[33] 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. 

[34] Data are reported for the quarter in which the activity occurred. 

[35] One study used a Wald estimator, a simple nonparametric 
regression. 

[36] 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. 

[37] 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. 

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