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
super sector 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 lay-off 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 estimating equations based on regression techniques. This
method, which underwent substantial enhancement at the beginning of 2005,
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 all nine census divisions and
the five additional substate areas contained in this release (the Cleveland-
Elyria-Mentor and Detroit-Warren-Livonia metropolitan areas and the Chicago-
Joliet-Naperville, Miami-Miami Beach-Kendall, and Seattle-Bellevue-Everett 
metropolitan divisions) and their respective balances of state are based on a
similar regression approach that does not incorporate CES or UI data. Estimates
for census regions are obtained by summing the model-based estimates for the
component divisions and then calculating the unemployment rate. Each month,
census division estimates are controlled to 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 request.

   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 reestimation. 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

   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

   Area definitions. The substate area data published in this release reflect
the standards and definitions established by the U.S. Office of Management and
Budget on December 1, 2009. 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, relatively small sample sizes limit the reliability
of the weighted link-relative estimates.  In these cases, BLS uses the CES small
domain model (SDM) to generate employment estimates. The SDM combines the direct
sample estimates (described above) and forecasts of historical (benchmarked) data
to decrease the volatility of the estimates. For more detailed information about
the CES small domain 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. In 2005, the LAUS program introduced several improvements
to its methodology. Among these were the development of model-based error measures
for the monthly estimates and the estimates of over-the-month changes. 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 0.9
point. More details can be found on the website. Measures of nonsampling error are
not available.

   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 380 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 7,400 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.

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Last Modified Date: January 27, 2015