Frequently Asked Questions
Questions and Answers
Local Area Unemployment Statistics (LAUS) Program Redesign for
on each question to show the answer.
- 1. What is the LAUS Redesign?
The LAUS Redesign is a multi-year,
multi-project initiative to improve labor force estimates for State
and substate areas developed by the LAUS program. Funding for the LAUS
Redesign research and implementation activities was initially provided
to BLS in FY 2001.
The LAUS Redesign includes:
- Improved time-series models for
currently modeled areas--all States, the District of Columbia, New
York City, the Los Angeles metropolitan area, and the respective
balances of New York and California.
- Real-time benchmarking to national Current Population
Survey (CPS) estimates and improved historical benchmarking of
model estimates to reliable national CPS estimates. (See question
4 for an explanation of real-time benchmarking.)
- The introduction of time series
models for up to six additional metropolitan areas (and respective
balances of States).
- Enhanced procedures for developing
other substate area LAUS estimates that employ innovative and
dynamic estimating methods.
- The implementation of 2000-Census
based configurations for metropolitan areas, metropolitan
divisions, micropolitan areas, and small labor market areas.
- The incorporation of 2000-Census
inputs and updates in the methodology.
When will the
LAUS Redesign changes be implemented?
- The changes will be implemented with
January 2005 estimates. Region and State labor force estimates will be
released on March 10, 2005, and metropolitan areas on March 18.
- 3. Why is BLS
making these changes?
A number of significant and
long-standing issues have been identified with the current method of
model estimation and annual benchmarking that affect accuracy and
analysis of the estimates. The current model approach does not provide
for error measures and requires external seasonal adjustment. The
current benchmarking method reintroduces sampling error into the
monthly series, which results in significant end-of-year revisions in
a number of States, causes discontinuities between
December-benchmarked and January-modeled estimates, introduces
spurious cyclical fluctuations, and does not adequately reflect the
effects of major national shocks to the economy in the State
The Redesign method of model
estimation will result in improved seasonal adjustment and provide
error measures on the seasonally adjusted and not seasonally adjusted
series. Real-time benchmarking to the national CPS measures will
ensure that national economic events are reflected in the State
estimates by requiring that all States add to the national CPS
estimates of employment and unemployment each month. The Redesign
method will significantly reduce end-of-year revision.
What are a
benchmark and real-time benchmarking?
- A benchmark is a reliable total to
which much less reliable estimates are controlled. For the LAUS
Redesign models, the reliable control total (benchmark) is the monthly
CPS national estimate of employment and unemployment. Real-time
benchmarking means that the adjustment to the reliable control total
(benchmarking) occurs as part of monthly estimation (in real-time).
The current method uses a State benchmark that is the CPS annual
average of employment and unemployment. The current benchmarking
method is historical in that we perform the correction
retrospectively, at the end of the year, after twelve months of
estimates are produced.
State labor force estimates to the U.S. levels? Why use the national
estimates of employment and unemployment as the monthly benchmark?
The monthly national CPS labor force
estimates provide an excellent benchmark because of its low variance.
The confidence interval on the monthly national unemployment rate is
±0.2 percentage point, and the sample design is such that a
difference of 0.2 percentage point in the unemployment rate over the
month is statistically significant.
In the current methodology, each
State’s model estimates are prepared independent of each other.
Although the monthly State CPS input data sum to the national
measures, the sum of State model estimates generally do not equal the
national CPS estimates. To evaluate model performance, each month the
sum of State model estimates is compared to the national CPS
estimates. Until 2001, the differences between the sum-of-State model
estimates and the national CPS were well within sampling error of the
national estimates. In 2001, significant deviations occurred in a
number of months, specifically March, August, and October-December,
when economic shocks to the economy related to the onset of the
recession and the September 11 terrorist attacks occurred. These
shocks were not adequately reflected in the State model estimates
because the model viewed much of the increase in State CPS
unemployment in these periods as related to sampling error. Large
benchmark revisions to annual average levels result from the model
dependence on historical data and its slow reaction to economic
The Redesign methodology requires the
monthly State employment and unemployment model estimates to add to
the national levels. This will preclude differences between the sum of
State estimates and the national estimates, ensure that national
shocks related to the business cycle or to an event such as the
terrorist attacks of September 11 will be addressed, and significantly
reduce annual revisions.
How do the new
Redesign models compare with the current models?
The current signal-plus-noise models
describe the CPS sample estimate as the sum of the true labor force
value (signal) and sampling error (noise). Two models, one for the
employment-population ratio and one for the unemployment rate, are
developed for each State, the District of Columbia, New York City, the
Los Angeles metropolitan area, and the respective balances of New York
and California. The model of the signal is combined with the model of
the error to arrive at the estimate of the true labor force value. In
estimating the signal, the employment-population ratio model uses the
ratio of statewide monthly estimate of workers on nonfarm payrolls to
intercensal population data as an explanatory variable, along with
flexible trend and seasonal variables. The unemployment rate model
uses the ratio of unemployment insurance claimants who file for the
CPS reference week to nonfarm payroll data, along with flexible trend
and seasonal variables. Seasonal adjustment is performed external to
the models, using X-11 ARIMA software. Benchmarking is performed to
the CPS annual average employment and unemployment levels for each
State and is accomplished retrospectively, at the end of each year.
The Redesign models are also
signal-plus-noise models, where the signal is a bivariate model of the
unemployment or employment levels. The unemployment insurance claims
and nonfarm payroll employment inputs themselves are modeled, as well
as their interaction with the appropriate CPS series. Seasonal, trend,
and irregular components are developed for each modeled estimate.
Seasonal adjustment occurs within the model structure through the
removal of the seasonal component. The models produce reliability
measures for the seasonally adjusted and not adjusted series, and on
over-the-month and over-the-year change. Each month, real-time
benchmarking occurs in a two-step process. Census division models are
constructed that are controlled to the national CPS. State models are
then controlled to their appropriate division estimates.
How are estimates
developed for the Census divisions?
- The nine Census divisions
geographically exhaust the nation. These groupings are currently used
to analyze and publish LAUS estimates. For LAUS estimation, the States
are grouped into these Census divisions for which models are developed
that provide reliable intermediate benchmark controls. Grouping States
also simplifies the computational and operational aspects of real-time
benchmarking. If all States were controlled directly to the national
total, a delay in one State would impact everyone. While the Census
division groupings have performed well, research will continue on
alternative aggregations for State control purposes.
Why are States
grouped into Census divisions? What is the rationale for using Census
divisions as intermediate controls?
- Statistics on the number of insured unemployed are collected as a byproduct of Unemployment Insurance (UI) programs. Workers who lose their jobs and are covered by these programs typically file claims, which serve as notice that they are beginning a period of unemployment. Claimants who qualify for benefits are counted in the insured unemployment figures. However, they only represent a portion of the total unemployed.
These data are not used to measure total unemployment because they exclude several important groups. The insured unemployed excludes unemployed workers who have exhausted their benefits; new entrants or reentrants to the labor market; disqualified workers whose unemployment is considered to have resulted from their own actions (misconduct on the job) rather than from economic conditions; and otherwise eligible unemployed persons who do not file for benefits.
In terms of employed workers, the principal groups not covered by the UI programs are self-employed workers, unpaid family workers, workers in certain non-profit organizations, and other, primarily seasonal, worker categories.
- 9. Because the State
totals are controlled to their Census division estimates, if a division
contains a large State, how will the monthly benchmark adjustment affect
other States in the division?
- The relative shares of each State’s
model estimates to its division total are preserved by the monthly
benchmark adjustment, but the absolute size of the adjustment to a
State’s monthly model estimate will be directly related to the size
of the model estimate. Thus, large States get larger adjustments than
small States. As a result, smaller States in a division will not be
dominated by one large State.
If a State in the
division has an atypical CPS value for the month, how will that affect
its estimates and the estimates of the other States in the division?
- The model for the State with an
atypical CPS value is likely to discount most of the atypical movement
as survey error. Because the estimated survey error is removed from
the State estimate before benchmarking is done, the atypical CPS value
will not affect the benchmark adjustment.
What are the advantages of the new estimating approach? What are the disadvantages?
The advantages of the new estimating
The disadvantages of the new estimating
- The production of reliability
measures on the seasonally adjusted and not seasonally adjusted
series and on over-the-month and over-the-year change, which will
enhance analysis of the series.
- Direct seasonal adjustment of
employment and unemployment, a methodological improvement.
- Greater understanding of the
contributions of the non-CPS model inputs (unemployment insurance
claims and nonfarm payroll employment) through bivariate modeling.
- Additivity to national and
division estimates of employment and unemployment each month, thus
ensuring the timely reflection of economic events in the State
- Reduction in the expected size of
the annual revisions to the State employment and unemployment
series through the use of real-time benchmarking to the national
- The use of Census divisions as an
intermediate estimation level requires interdependence of
estimation among States in the division. States will no longer be
able to produce final labor force estimates on their own.
- Interdependence of estimation
makes the approach vulnerable in the event of missing State data.
To preclude that, provision has been made to temporarily
substitute model predictions for missing State data in the
production of labor force estimates.
- The official annual averages of
employment and unemployment for States from the LAUS program will
no longer be identical to the sample-based annual average
estimates from the CPS published in Geographic Profile of
Employment and Unemployment.
Why is modeling as a technique superior to the direct use of household survey data?
- The State CPS estimate for a given
month is based on the corresponding sample for that month, which is
too small to provide a reliable estimate. For most small States, the
monthly CPS sample-based unemployment rate has a confidence interval
of ±1.6 percentage points at the 90 percent level of confidence,
which means that the rate must change by that amount to be considered
significant. In contrast, the model estimates are based on the entire
historical CPS series, beginning in 1976, as well as related series on
unemployment insurance claimants and payroll employment. Based on this
larger set of information, the models are able to provide much more
stable estimates of employment and unemployment than is possible with
the individual CPS sample estimates. In general, a change of ± 0.5
percentage point in the model estimate will be statistically
significant. Also, adequate seasonal adjustment of the highly variable
monthly CPS series is not possible, while the model will produce
seasonally adjusted series.
Are the new
models more accurate and reliable than the current models?
- Yes. The current model cannot produce
measures of error for the seasonally adjusted estimates, which makes
it difficult to judge its reliability. The Redesign model will produce
measures of error for both seasonally adjusted and not seasonally
adjusted series, and for over-the-month and over-the-year change.
Significant improvements in accuracy and reliability of the Redesign
estimates reflect the provision of more comprehensive error measures
and the use of real-time benchmarking to monthly levels of national
employment and unemployment. Monthly national CPS data are more
reliable than the State annual average estimates. At the end of the
year, the current method puts much of the sampling error back into the
estimates through benchmarking to State CPS annual averages. The
Redesign method reduces both sampling error and bias in the estimates.
Can I still use
the State CPS annual average demographic data published in Geographic
Profile of Employment and Unemployment?
Yes. However, the 2005 data issued in Geographic Profile will not be equal to the official LAUS
program estimates for employment and unemployment for States and
published areas. The State and area data published in Geographic
Profile are CPS sample-based estimates. The CPS is designed to
produce annual average State labor force data with an 8 percent or
less coefficient of variation on the level of unemployment when the
unemployment rate is 6 percent. The CPS State labor force estimates
contain more variance than the model-based estimates, because the
latter will reflect a national CPS benchmark as well as advanced
modeling techniques. (In fact, the Redesign model estimates will have
a coefficient of variation of approximately half that of the CPS.)
Although the annual average State CPS
estimates will not be the official LAUS estimates, the State CPS
sample does generate demographic information. While these estimates
contain significant sampling error, they do provide important,
relatively timely information on the characteristics of the State
labor force and can be used in that regard. The annual average
metropolitan area and central city data from the CPS also will not
match the official LAUS estimates. These CPS data are highly variable
as well, and are published to provide demographic detail.
- 15.How will the
Redesign State models impact estimates for metropolitan areas, counties,
As part of the LAUS program Redesign,
models are under development for the following areas and the
respective balance-of-State areas: Chicago metropolitan division,
Cleveland, Detroit metropolitan division, Miami, New Orleans, and
Seattle-Everett metropolitan division. These models will follow the
division form (univariate), will be benchmarked to the State
employment and unemployment estimates on a real-time basis, and will
be implemented with estimates for January 2005. Detailed information
on area models will be issued shortly.
For areas other than those listed
above, all substate areas in the State will be controlled to add to
the monthly State estimates of employment and unemployment, as is the
case with the current methodology. So, improvements in State
estimation will be reflected in these substate estimates.
Are the Redesign
model estimates being tested prior to implementation?
Yes. During 2004, all States are
participating in a year-long period of dual estimation where estimates
are made using both the current and Redesign model methodologies.
Formal feedback on the Redesign models was provided to BLS in July,
and additional feedback will be provided through the end of the year.
The new estimates differ from current
estimates for the same period because of the improved modeling
approach and the use of real-time benchmarking to monthly national
employment and unemployment. The latter innovation allows the models
to better reflect current economic activity.
- 17.Generally, how do
the Redesign unemployment rates compare to the current official
- In the first six months of dual
estimation, monthly estimates of the unemployment rate (not seasonally
adjusted) developed using the Redesign method are somewhat higher than
the rates based on the current official method. About 13 percent of
the Redesign State monthly jobless rates were lower than the current
estimates, 8 percent were the same, and 79 percent were higher. Where
the Redesign estimate was higher, about half had differences of 0.2
percentage point or less, and half had higher. The differences vary by
month and by State and reflect the individual State’s inputs and
their interactions, the interaction of the State with other States in
the division, and the national economy. However, additional months may
affect these results.
Are the current
official estimates wrong?
- No. The current estimates are based
on the modeling and benchmarking approach that reflected
state-of-the-art methodology and operations in 1994. To the extent
possible, improvements were made in the years leading up to the
proposed approach. Moreover, until the completion of the dual
estimation period, the Redesign estimates should be considered
Does the Redesign
model methodology change affect when labor force estimates will be
released each month?
In the Redesign system, States enter
their nonfarm payroll employment and unemployment insurance claimant
input information the same way they do in the current system. However,
final estimates cannot be made until all States in the relevant Census
division have provided their inputs. (This contrasts with the current
estimation where States are able to produce final estimates
independently.) The final estimates for each Census division grouping
of States are produced once all inputs have been provided to BLS.
The use of the Redesign models and
methods will not impact the BLS release of State labor force
How will the LAUS
Redesign affect historical comparisons?
- The entire historical series from
January 1976 forward will be replaced with estimates based on the
Redesign models (thus extending the length of the series by 2 years).
The revised historical data will also be available on the BLS website.
Will the States
and areas still be benchmarked at the end of the year? What will be
updated and benchmarked?
State estimates are benchmarked to
the national CPS estimates of employment and unemployment each month
via the Census division models. A modified annual historical
benchmarking will still occur at the end of the year. It will involve
updating of model inputs and population controls, model re-estimation,
smoothing, and controlling to revised monthly historical benchmarked
estimates at the division level, which in turn will sum to the monthly
national CPS estimates.
While the effect of the Redesign
models with real-time benchmarking will differ by State, it is
expected that the annual revisions to employment and unemployment will
be smaller than was experienced with the current models.
When will a
fourth generation of models be introduced?
- Since the introduction of the first
generation of models in 1989, BLS has maintained a continuous program
of research to develop further improvements to the models. Major
advancements were introduced in 1994. Following the planned upgrade in
2005, work on model refinements will continue but major improvements
on the level of a new generation will not be forthcoming for many
Where can I go to
get technical information on the Redesign models?
- See "Proposed Improvement in
Estimating and Benchmarking State Labor Force Estimates" (PDF 98 K).