Regional and State Unemployment, 2016 Annual Average Technical Note

Technical Note

This release presents labor force and unemployment data for census regions and divisions
and states from the Local Area Unemployment Statistics (LAUS) program. The LAUS program
is a federal-state cooperative endeavor.


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 employed
and unemployed persons on a place-of-residence basis. The universe for each is the
civilian noninstitutional population 16 years of age and older. 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 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 persons expressed as a percent of the labor force. The employment-population
ratio is the proportion of the civilian noninstitutional population 16 years of age and 
older that is employed.

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 uses data from several sources, including the CPS,
the Current Employment Statistics (CES) survey of nonfarm payroll employment, 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 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. 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 beginning of each year. The adjusted estimates incorporate updated population
controls from the U.S. Census Bureau, any revisions in the other data sources, and model
re-estimation. The population controls reflect extrapolation from the 2010 Census. In
most years, historical data for the most recent 5 years (both seasonally adjusted and
not seasonally adjusted) are revised near the beginning of each calendar year, prior to
the release of January estimates. Though the labor force estimates typically are updated
for 5 years, the population estimates are revised back to the decennial estimates base
(April 2010).

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. In table 1, level
estimates for states may not sum to level estimates for regions and divisions because of
rounding. Unemployment rates and employment-population ratios are computed from unrounded
levels and, thus, may differ slightly from rates and ratios computed using the rounded
level estimates displayed in table 1.

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 employment-population ratios regardless of their statistical significance. The
remainder of the analysis in the release—other than historical highs and lows—takes
statistical significance into consideration. Model-based error measures are available
online at BLS uses 90-percent confidence levels in
determining whether changes in LAUS unemployment rates and employment-population ratios
are statistically significant. The average magnitude of the over-the-year change in an
annual state unemployment rate that is required in order to be statistically significant
at the 90-percent confidence level is about 0.4 percentage point. The average magnitude
of the over-the-year change in an annual state employment-population ratio that is
required in order to be statistically significant at the 90-percent confidence level is
about 0.6 percentage point. Measures of nonsampling error are not available.

Additional information
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: February 28, 2017