Washington, DC...Total nonfarm payroll employment increased by 195,000 in June, and the unemployment rate was unchanged at 7.6 percent, the U.S. Bureau of Labor Statistics reported today. Employment rose in leisure and hospitality, professional and business services, retail trade, health
care, and financial activities....

Frequently Asked Questions about Employment and Unemployment Estimates



1. Why are there two monthly measures of employment?



   The household survey and establishment survey both produce sample-based estimates

   of   employment, and both have strengths and limitations. The establishment survey

   employment series has a   smaller margin of error on the measurement of month-to-

   month change   than the household survey because of its much larger sample size. An

   over-the-month employment change of about 100,000 is statistically significant in

   the establishment survey, while the threshold for a statistically significant change

   in the household survey is about 400,000. However, the household survey has a more

   expansive scope than the establishment survey because it includes self-employed

   workers whose businesses are unincorporated, unpaid family workers, agricultural

   workers, and private household workers, who are excluded by the establishment survey.

   The household survey also provides estimates of employment for demographic groups.

   For more information on the differences between the two surveys, please visit

   www.bls.gov/web/empsit/ces_cps_trends.pdf.



2. Are undocumented immigrants counted in the surveys?



   It is likely that both surveys include at least some undocumented immigrants. However,

   neither the establishment nor the household survey is designed to identify the legal

   status of workers. Therefore, it is not possible to determine how many are counted in

   either survey. The establishment survey does not collect data on the legal status of

   workers. The household survey does include questions which identify the foreign and

   native born, but it does not include questions about the legal status of the foreign

   born. Data on the foreign and native born are published each month in table A-7 of

   The Employment Situation news release.



3. Why does the establishment survey have revisions?



   The establishment survey revises published estimates to improve its data series by

   incorporating additional information that was not available at the time of the

   initial publication of the estimates. The establishment survey revises its initial

   monthly estimates twice, in the immediately succeeding 2 months, to incorporate

   additional sample receipts from respondents in the survey and recalculated seasonal

   adjustment factors. For more information on the monthly revisions, please visit

   www.bls.gov/ces/cesrevinfo.htm.



   On an annual basis, the establishment survey incorporates a benchmark revision that

   re-anchors estimates to nearly complete employment counts available from unemployment

   insurance tax records. The benchmark helps to control for sampling and modeling errors

   in the estimates. For more information on the annual benchmark revision, please visit

   www.bls.gov/web/empsit/cesbmart.htm.



4. Does the establishment survey sample include small firms?



   Yes; about 40 percent of the establishment survey sample is comprised of business

   establishments with fewer than 20 employees. The establishment survey sample is

   designed to maximize the reliability of the statewide total nonfarm employment

   estimate; firms from all states, size classes, and industries are appropriately

   sampled to achieve that goal.



5. Does the establishment survey account for employment from new businesses?



   Yes; monthly establishment survey estimates include an adjustment to account for

   the net employment change generated by business births and deaths. The adjustment

   comes from an econometric model that forecasts the monthly net jobs impact of

   business births and deaths based on the actual past values of the net impact that

   can be observed with a lag from the Quarterly Census of Employment and Wages. The

   establishment survey uses modeling rather than sampling for this purpose because

   the survey is not immediately able to bring new businesses into the sample. There

   is an unavoidable lag between the birth of a new firm and its appearance on the

   sampling frame and availability for selection. BLS adds new businesses to the survey

   twice a year.



6. Is the count of unemployed persons limited to just those people receiving unemployment

   insurance benefits?



   No; the estimate of unemployment is based on a monthly sample survey of households.

   All persons who are without jobs and are actively seeking and available to work are

   included among the unemployed. (People on temporary layoff are included even if

   they do not actively seek work.) There is no requirement or question relating to

   unemployment insurance benefits in the monthly survey.



7. Does the official unemployment rate exclude people who want a job but are not currently

   looking for work?



   Yes; however, there are separate estimates of persons outside the labor force who

   want a job, including those who are not currently looking because they believe no

   jobs are available (discouraged workers). In addition, alternative measures of labor

   underutilization (some of which include discouraged workers and other groups not

   officially counted as unemployed) are published each month in table A-15 of The

   Employment Situation news release. For more information about these alternative

   measures, please visit www.bls.gov/cps/lfcharacteristics.htm#altmeasures.



8. How can unusually severe weather affect employment and hours estimates?



   In the establishment survey, the reference period is the pay period that includes

   the 12th of the month. Unusually severe weather is more likely to have an impact on

   average weekly hours than on employment. Average weekly hours are estimated for paid

   time during the pay period, including pay for holidays, sick leave, or other time off.

   The impact of severe weather on hours estimates typically, but not always, results in

   a reduction in average weekly hours. For example, some employees may be off work for

   part of the pay period and not receive pay for the time missed, while some workers,

   such as those dealing with cleanup or repair, may work extra hours.



   In order for severe weather conditions to reduce the estimate of payroll employment,

   employees have to be off work without pay for the entire pay period. Slightly more

   than 20 percent of all employees in the payroll survey sample have a weekly pay

   period. Employees who receive pay for any part of the pay period, even 1 hour, are

   counted in the payroll employment figures. It is not possible to quantify the effect

   of extreme weather on estimates of over-the-month change in employment.



   In the household survey, the reference period is generally the calendar week that

   includes the 12th of the month. Persons who miss the entire week's work for weather-

   related events are counted as employed whether or not they are paid for the time

   off. The household survey collects data on the number of persons who had a job but

   were not at work due to bad weather. It also provides a measure of the number of

   persons who usually work full time but had reduced hours. Current and historical

   data are available on the  household survey's most requested statistics page at

   http://data.bls.gov/cgi-bin/surveymost?ln.

Technical Note



   This news release presents statistics from two major surveys, the Current

Population Survey (CPS; household survey) and the Current Employment Statistics

survey (CES; establishment survey). The household survey provides information

on the labor force, employment, and unemployment that appears in the "A" tables,

marked HOUSEHOLD DATA. It is a sample survey of about 60,000 eligible households

conducted by the U.S. Census Bureau for the U.S. Bureau of Labor Statistics (BLS).



   The establishment survey provides information on employment, hours, and

earnings of employees on nonfarm payrolls; the data appear in the "B" tables,

marked ESTABLISHMENT DATA. BLS collects these data each month from the payroll

records of a sample of nonagricultural business establishments. Each month

the CES program surveys about 145,000 businesses and government agencies,

representing approximately 557,000 individual worksites, in order to provide

detailed industry data on employment, hours, and earnings of workers on nonfarm

payrolls. The active sample includes approximately one-third of all nonfarm

payroll employees.



   For both surveys, the data for a given month relate to a particular week or

pay period. In the household survey, the reference period is generally the

calendar week that contains the 12th day of the month. In the establishment

survey, the reference period is the pay period including the 12th, which may or

may not correspond directly to the calendar week.



Coverage, definitions, and differences between surveys



   Household survey. The sample is selected to reflect the entire civilian 

noninstitutional population. Based on responses to a series of questions on 

work and job search activities, each person 16 years and over in a sample

household is classified as employed, unemployed, or not in the labor force.



   People are classified as employed if they did any work at all as paid employees

during the reference week; worked in their own business, profession, or on their

own farm; or worked without pay at least 15 hours in a family business or farm.

People are also counted as employed if they were temporarily absent from their jobs

because of illness, bad weather, vacation, labor-management disputes, or personal

reasons.



   People are classified as unemployed if they meet all of the following criteria:

they had no employment during the reference week; they were available for work at

that time; and they made specific efforts to find employment sometime during the

4-week period ending with the reference week. Persons laid off from a job and

expecting recall need not be looking for work to be counted as unemployed. The

unemployment data derived from the household survey in no way depend upon the

eligibility for or receipt of unemployment insurance benefits.



   The civilian labor force is the sum of employed and unemployed persons.

Those persons not classified as employed or unemployed are not in the labor 

force. The unemployment rate is the number unemployed as a percent of the 

labor force. The labor force participation rate is the labor force as a 

percent of the population, and the employment-population ratio is the 

employed as a percent of the population. Additional information about the 

household survey can be found at www.bls.gov/cps/documentation.htm.



   Establishment survey. The sample establishments are drawn from private

nonfarm businesses such as factories, offices, and stores, as well as

from federal, state, and local government entities. Employees on nonfarm

payrolls are those who received pay for any part of the reference pay

period, including persons on paid leave. Persons are counted in each job

they hold. Hours and earnings data are produced for the private sector for

all employees and for production and nonsupervisory employees. Production

and nonsupervisory employees are defined as production and related employees

in manufacturing and mining and logging, construction workers in construction,

and nonsupervisory employees in private service-providing industries.



   Industries are classified on the basis of an establishment’s principal

activity in accordance with the 2012 version of the North American Industry

Classification System. Additional information about the establishment survey

can be found at www.bls.gov/ces/.



   Differences in employment estimates. The numerous conceptual and methodological

differences between the household and establishment  surveys result in important

distinctions in the employment estimates derived from the surveys. Among these are:



   --The household survey includes agricultural workers, self-employed workers

     whose businesses are unincorporated, unpaid family workers, and private

     household workers among the employed. These groups are excluded from the

     establishment survey.



   --The household survey includes people on unpaid leave among the employed.

     The establishment survey does not.



   --The household survey is limited to workers 16 years of age and older.

     The establishment survey is not limited by age.



   --The household survey has no duplication of individuals, because

     individuals are counted only once, even if they hold more than one

     job. In the establishment survey, employees working at more than one

     job and thus appearing on more than one payroll are counted separately

     for each appearance.



Seasonal adjustment



   Over the course of a year, the size of the nation's labor force and the levels

of employment and unemployment undergo regularly occurring fluctuations. These 

events may result from seasonal changes in weather, major holidays, and the opening

and closing of schools. The effect of such seasonal variation can be very large.



   Because these seasonal events follow a more or less regular pattern each year,

their influence on the level of a series can be tempered by adjusting for regular

seasonal variation. These adjustments make nonseasonal developments, such as

declines in employment or increases in the participation of women in the labor

force, easier to spot. For example, in the household survey, the large number of

youth entering the labor force each June is likely to obscure any other changes

that have taken place relative to May, making it difficult to determine if the 

level of economic activity has risen or declined. Similarly, in the establishment

survey, payroll employment in education declines by about 20 percent at the end

of the spring term and later rises with the start of the fall term, obscuring the

underlying employment trends in the industry. Because seasonal employment changes

at the end and beginning of the school year can be estimated, the statistics can be

adjusted to make underlying employment patterns more discernable.  The seasonally

adjusted figures provide a more useful tool with which to analyze changes in

month-to-month economic activity.



   Many seasonally adjusted series are independently adjusted in both the household

and establishment surveys. However, the adjusted series for many major estimates,

such as total payroll employment, employment in most major sectors, total employment,

and unemployment are computed by aggregating independently adjusted component series.

For example, total unemployment is derived by summing the adjusted series for four

major age-sex components; this differs from the unemployment estimate that would be

obtained by directly adjusting the total or by combining

the duration, reasons, or more detailed age categories.



   For both the household and establishment surveys, a concurrent seasonal adjustment

methodology is used in which new seasonal factors are calculated each month using all

relevant data, up to and including the data for the current month. In the household

survey, new seasonal factors are used to adjust only the current month's data. In the

establishment survey, however, new seasonal factors are used each month to adjust the

three most recent monthly estimates. The prior 2 months are routinely revised to

incorporate additional sample reports and recalculated seasonal adjustment factors.

In both surveys, 5-year revisions to historical data are made once a year.



Reliability of the estimates



   Statistics based on the household and establishment surveys are subject to both

sampling and nonsampling error. When a sample, rather than the entire population,

is surveyed, there is a chance that the sample estimates may differ from the true

population values they represent. The component of this difference that occurs

because samples differ by chance is known as sampling error, and its variability

is measured by the standard error of the estimate. There is about a 90-percent

chance, or level of confidence, that an estimate based on a sample will differ by

no more than 1.6 standard errors from the true population value because of sampling

error. BLS analyses are generally conducted at the 90-percent level of confidence.



   For example, the confidence interval for the monthly change in total nonfarm

employment from the establishment survey is on the order of plus or minus 90,000.

Suppose the estimate of nonfarm employment increases by 50,000 from one month to

the next. The 90-percent confidence interval on the monthly change would range from

-40,000 to +140,000 (50,000 +/- 90,000). These figures do not mean that the sample

results are off by these magnitudes, but rather that there is about a 90-percent

chance that the true over-the-month change lies within this interval. Since this

range includes values of less than zero, we could not say with confidence that

nonfarm employment had, in fact, increased that month. If, however, the reported

nonfarm employment rise was 250,000, then all of the values within the 90- percent

confidence interval would be greater than zero. In this case, it is likely (at

least a 90-percent chance) that nonfarm employment had, in fact, risen that month.

At an unemployment rate of around 6.0 percent, the 90-percent confidence interval

for the monthly change in unemployment as measured by the household survey is

about +/- 300,000, and for the monthly change in the unemployment rate it is about

+/- 0.2 percentage point.



   In general, estimates involving many individuals or establishments have lower

standard errors (relative to the size of the estimate) than estimates which are based

on a small number of observations. The precision of estimates also is improved when

the data are cumulated over time, such as for quarterly and annual averages.



   The household and establishment surveys are also affected by nonsampling error,

which can occur for many reasons, including the failure to sample a segment of the

population, inability to obtain information for all respondents in the sample,

inability or unwillingness of respondents to provide correct information on a

timely basis, mistakes made by respondents, and errors made in the collection or

processing of the data.



   For example, in the establishment survey, estimates for the most recent 2 months

are based on incomplete returns; for this reason, these estimates are labeled

preliminary in the tables. It is only after two successive revisions to a monthly

estimate, when nearly all sample reports have been received, that the estimate is

considered final.



   Another major source of nonsampling error in the establishment survey is the

inability to capture, on a timely basis, employment generated by new firms. To

correct for this systematic underestimation of employment growth, an estimation

procedure with two components is used to account for business births. The first

component excludes employment losses from business deaths from sample-based

estimation in order to offset the missing employment gains from business births.

This is incorporated into the sample-based estimation procedure by simply not

reflecting sample units going out of business, but imputing to them the same

employment trend as the other firms in the sample. This procedure accounts for

most of the net birth/death employment.



   The second component is an ARIMA time series model designed to estimate the

residual net birth/death employment not accounted for by the imputation. The

historical time series used to create and test the ARIMA model was derived from

the unemployment insurance universe micro- level database, and reflects the actual

residual net of births and deaths over the past 5 years.



   The sample-based estimates from the establishment survey are adjusted once a

year (on a lagged basis) to universe counts of payroll employment obtained from

administrative records of the unemployment insurance program. The difference 

between the March sample-based employment estimates and the March universe counts

is known as a benchmark revision, and serves as a rough proxy for total survey

error. The new benchmarks also incorporate changes in the classification of

industries. Over the past decade, absolute benchmark revisions for total nonfarm

employment have averaged 0.3 percent, with a range from -0.7 to 0.6 percent.



Other 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.