Regional and State Employment and Unemployment Technical Note

Technical Note

   This release presents labor force and unemployment data for census regions and
divisions, states, and selected substate areas from the Local Area Unemployment
Statistics (LAUS) program (tables 1 to 4). Also presented are nonfarm payroll
employment estimates by state and industry supersector from the Current Employment
Statistics (CES) program (tables 5 and 6). The LAUS and CES programs are both
federal-state cooperative endeavors.

Labor force and unemployment--from the LAUS program

   Definitions. The labor force and unemployment data are based on the same concepts
and definitions as those used for the official national estimates obtained from the
Current Population Survey (CPS), a sample survey of households that is conducted
for the Bureau of Labor Statistics (BLS) by the U.S. Census Bureau. The LAUS program
measures employment and unemployment on a place-of-residence basis. The universe for
each is the civilian noninstitutional population 16 years of age and over. Employed
persons are those who did any work at all for pay or profit in the reference week
(the week including the 12th of the month) or worked 15 hours or more without pay
in a family business or farm, plus those not working who had a job from which they
were temporarily absent, whether or not paid, for such reasons as bad weather,
labor-management dispute, illness, or vacation. Unemployed persons are those who
were not employed during the reference week (based on the definition above), had
actively looked for a job sometime in the 4-week period ending with the reference
week, and were currently available for work; persons on layoff expecting recall
need not be looking for work to be counted as unemployed. The labor force is the
sum of employed and unemployed persons. The unemployment rate is the number of
unemployed as a percent of the labor force.

   Method of estimation. Estimates for 48 of the 50 states, the District of Columbia,
the Los Angeles-Long Beach-Glendale metropolitan division, New York City, and the
balances of California and New York State are produced using time-series models.
This method, which underwent substantial enhancement at the beginning of 2015,
utilizes data from several sources, including the CPS, the CES, and state
unemployment insurance (UI) programs. Estimates for the state of California
are derived by summing the estimates for the Los Angeles-Long Beach-Glendale
metropolitan division and the balance of California. Similarly, estimates for
New York State are derived by summing the estimates for New York City and the
balance of New York State. Estimates for the nine census divisions, as well as
the five additional substate areas contained in this release (the Cleveland-Elyria
and Detroit-Warren-Dearborn metropolitan areas and the Chicago-Naperville-Arlington
Heights, Miami-Miami Beach-Kendall, and Seattle-Bellevue-Everett metropolitan
divisions) and their respective balances of state are based on similar model-based 
approaches. Estimates for census regions are obtained by summing the model-based
estimates for the component divisions. Each month, census division estimates are
controlled to the national totals; state estimates are then controlled to their
respective division totals. Substate and balance-of-state estimates for the five
areas noted above are controlled to their respective state totals. Estimates for
Puerto Rico are derived from a monthly household survey similar to the CPS. A
detailed description of the estimation procedures is available from BLS upon

   Annual revisions. Labor force and unemployment data for prior years reflect
adjustments made at the end of each year. The adjusted estimates reflect updated
population data from the U.S. Census Bureau, any revisions in the other data
sources, and model re-estimation. In most years, historical data for the most
recent five years (both seasonally adjusted and not seasonally adjusted) are
revised near the beginning of each calendar year, prior to the release of January
estimates. With the introduction of a new generation of times-series models in
early 2015, historical data were re-estimated back to the series beginnings in
1976, 1990, or 1994.

   Seasonal adjustment. The LAUS program introduced smoothed seasonally adjusted (SSA)
estimates in January 2010. These are seasonally adjusted data that have incorporated
a long-run trend smoothing procedure, resulting in estimates that are less volatile
than those previously produced. The estimates are smoothed using a Henderson Trend
Filter (H13). The H13 uses a filtering procedure, based on moving averages, to remove
the irregular fluctuations from the seasonally adjusted series, leaving the trend. The
same process is used on both historical and current year estimates. For more information
about the smoothing technique, see the BLS website at 

   Area definitions. The substate area data published in this release reflect the
delineations issued by the U.S. Office of Management and Budget on February 28, 2013.
A detailed list of the geographic definitions is available online at 

Employment--from the CES program

   Definitions. Employment data refer to persons on establishment payrolls who receive pay
for any part of the pay period that includes the 12th of the month. Persons are counted
at their place of work rather than at their place of residence; those appearing on more
than one payroll are counted on each payroll. Industries are classified on the basis
of their principal activity in accordance with the 2012 version of the North American
Industry Classification System.

   Method of estimation. CES State and Area employment data are produced using several
estimation procedures. Where possible these data are produced using a "weighted link
relative" estimation technique in which a ratio of current month weighted employment to
that of the previous-month weighted employment is computed from a sample of establishments
reporting for both months. The estimates of employment for the current month are then
obtained by multiplying these ratios by the previous month's employment estimates. The
weighted link relative technique is utilized for data series where the sample size meets
certain statistical criteria. 

   For some employment series, the sample of establishments is very small or highly
variable. In these cases, a model-based approach is used in estimation. These models
use the direct sample estimates (described above), combined with forecasts of historical
(benchmarked) data to decrease volatility in estimation. Two different models (Fay-Herriot
Model and Small Domain Model) are used depending on the industry level being estimated.
For more detailed information about each model, refer to the BLS Handbook of Methods.

   Annual revisions. Employment estimates are adjusted annually to a complete count of
jobs, called benchmarks, derived principally from tax reports that are submitted by
employers who are covered under state unemployment insurance (UI) laws. The benchmark
information is used to adjust the monthly estimates between the new benchmark and the
preceding one and also to establish the level of employment for the new benchmark month.
Thus, the benchmarking process establishes the level of employment, and the sample is
used to measure the month-to-month changes in the level for the subsequent months.

   Seasonal adjustment. Payroll employment data are seasonally adjusted at the statewide
supersector level. In some states, the seasonally adjusted payroll employment total is
computed by aggregating the independently adjusted supersector series. In other states,
the seasonally adjusted payroll employment total is independently adjusted. Revisions of
historical data for the most recent 5 years are made once a year, coincident with annual
benchmark adjustments.

   Caution on aggregating state data. State estimation procedures are designed to produce
accurate data for each individual state. BLS independently develops a national employment
series; state estimates are not forced to sum to national totals. Because each state
series is subject to larger sampling and nonsampling errors than the national series,
summing them cumulates individual state level errors and can cause significant distortions
at an aggregate level. Due to these statistical limitations, BLS does not compile a "sum-
of-states" employment series, and cautions users that such a series is subject to a
relatively large and volatile error structure.

Reliability of the estimates

   The estimates presented in this release are based on sample surveys, administrative
data, and modeling and, thus, are subject to sampling and other types of errors. Sampling
error is a measure of sampling variability--that is, variation that occurs by chance
because a sample rather than the entire population is surveyed. Survey data also are
subject to nonsampling errors, such as those which can be introduced into the data
collection and processing operations. Estimates not directly derived from sample surveys
are subject to additional errors resulting from the specific estimation processes used.
The sums of individual items may not always equal the totals shown in the same tables
because of rounding. Unemployment rates are computed from unrounded data and thus may
differ slightly from rates computed using the rounded data displayed in the tables.

   Use of error measures. The introductory section of this release preserves the long-
time practice of highlighting the direction of the movements in regional and state
unemployment rates and state nonfarm payroll employment regardless of their statistical
significance. The remainder of the analysis in the release takes statistical significance
into consideration. 

   Labor force and unemployment estimates. Model-based error measures for seasonally
adjusted and not seasonally adjusted data and for over-the-month and over-the-year
changes are available online at BLS uses a 90-percent
confidence level in determining whether changes in LAUS unemployment rates are
statistically significant. The average magnitude of the current year over-the-month
change in a state unemployment rate that is required for statistical significance at
the 90-percent confidence level is just over 0.2 percentage point; the average amount
of the current over-the-year change in a state rate for significance is about 0.7
point. More details can be found on the website. Measures of nonsampling error are not

Employment estimates. Measures of sampling error for state CES data at the total nonfarm
and supersector levels are available online at BLS uses a
90-percent confidence level in determining whether changes in CES employment levels are
statistically significant. Information on recent benchmark revisions for states is
available online at 

Additional information

Estimates of labor force and unemployment from the LAUS program, as well as nonfarm
employment from the CES program, for 394 metropolitan areas and metropolitan New
England City and Town Areas (NECTAs) are available in the news release, Metropolitan
Area Employment and Unemployment. Estimates of labor force, employment, and unemployment
for approximately 7,500 subnational areas are available online at
Employment data from the CES program for states and metropolitan areas are available
online at Information in this release will be made available to sensory
impaired individuals upon request. Voice phone: (202) 691-5200; Federal Relay Service:
(800) 877-8339.

Table of Contents

Last Modified Date: April 15, 2016