Unemployment Insurance
More Guidance and Evaluation of Worker-Profiling Initiative Could Help Improve State Efforts Gao ID: GAO-07-680 June 14, 2007Changes 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.
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.
RecommendationsOur recommendations from this work are listed below with a Contact for more information. Status will change from "In process" to "Open," "Closed - implemented," or "Closed - not implemented" based on our follow up work.
Director: Team: Phone:GAO-07-680, Unemployment Insurance: More Guidance and Evaluation of Worker-Profiling Initiative Could Help Improve State Efforts
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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]
Related GAO Products:
Workforce Investment Act: Employers Found One-Stop Centers Useful in
Hiring Low-Skilled Workers; Performance Information Could Help Gauge
Employer Involvement. GAO-07-167. Washington, D.C.: December 22, 2006.
Unemployment Insurance: States' Tax Financing Systems Allow Costs to Be
Shared among Industries. GAO-06-769. Washington, D.C.: July 26, 2006.
Unemployment Insurance: Enhancing Program Performance by Focusing on
Improper Payments and Reemployment Services. GAO-06-696T. Washington,
D.C.: May 4, 2006.
Unemployment Insurance: Factors Associated with Benefit Receipt and
Linkages with Reemployment Services for Claimants. GAO-06-484T.
Washington, D.C.: March, 15, 2006.
Unemployment Insurance: Factors Associated with Benefit Receipt. GAO-
06-341. Washington, D.C.: March 7, 2006.
Workforce Investment Act: Labor and States Have Taken Actions to
Improve Data Quality, but Additional Steps Are Needed. GAO-06-82.
Washington, D.C.: November 14, 2005.
Unemployment Insurance: Better Data Needed to Assess Reemployment
Services to Claimants. GAO-05-413. Washington, D.C.: June 24, 2005.
Workforce Investment Act: Labor Should Consider Alternative Approaches
to Implement New Performance and Reporting Requirements. GAO-05-539.
Washington, D.C.: May 27, 2005.
Unemployment Insurance: Information on Benefit Receipt. GAO-05-291.
Washington, D.C. March 17, 2005.
Workforce Investment Act: Employers Are Aware of, Using, and Satisfied
with One-Stop Services, but More Data Could Help Labor Better Address
Employers' Needs. GAO-05-259. Washington, D.C.: February 18, 2005.
Workforce Investment Act: States and Local Areas Have Developed
Strategies to Assess Performance, but Labor Could Do More to Help. GAO-
04-657. Washington, D.C.: June 1, 2004.
Workforce Investment Act: One-Stop Centers Implemented Strategies to
Strengthen Services and Partnerships, but More Research and Information
Sharing Is Needed. GAO-03-725. Washington, D.C.: June: 18, 2003.
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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