July 2025 Bureau of Labor Statistics – Employment Situation Summary

Aug 2, 2025 04:50 PM EDT, Sat

Employment Situation Summary - 2025 M07 Results

Transmission of material in this news release is embargoed until USDL-25-1202 8:30 a.m. (ET) Friday, August 1, 2025

Technical information:

       
Household data: (202) 691-6378 cpsinfo@bls.gov www.bls.gov/cps</a>
Establishment data: (202) 691-6555 cesinfo@bls.gov www.bls.gov/ces
Media contact: (202) 691-5902 PressOffice@bls.gov  

THE EMPLOYMENT SITUATION – JULY 2025

Total nonfarm payroll employment changed little in July (+73,000) and has shown little change since April, the U.S. Bureau of Labor Statistics (BLS) reported today. The unemployment rate, at 4.2 percent, also changed little in July. Employment continued to trend up in health care and in social assistance. Federal government continued to lose jobs.

This news release presents statistics from two monthly surveys. The household survey measures labor force status, including unemployment, by demographic characteristics. The establishment survey measures nonfarm employment, hours, and earnings by industry. For more information about the concepts and statistical methodology used in these two surveys, see the Technical Note.

Household Survey Data

Both the unemployment rate, at 4.2 percent, and the number of unemployed people, at 7.2 million, changed little in July. The unemployment rate has remained in a narrow range of 4.0 percent to 4.2 percent since May 2024. (See table A-1.)

Among the major worker groups, the unemployment rates for adult men (4.0 percent), adult women (3.7 percent), teenagers (15.2 percent), Whites (3.7 percent), Blacks (7.2 percent), Asians (3.9 percent), and Hispanics (5.0 percent) showed little change in July. (See tables A-1, A-2, and A-3.)

Among the unemployed, the number of new entrants increased by 275,000 in July to 985,000. New entrants are unemployed people who are looking for their first job. (See table A-11.)

In July, the number of long-term unemployed (those jobless for 27 weeks or more) increased by 179,000 to 1.8 million. The long-term unemployed accounted for 24.9 percent of all unemployed people. (See table A-12.)

The labor force participation rate, at 62.2 percent, changed little in July but has declined by 0.5 percentage point over the year. The employment-population ratio, at 59.6 percent, also changed little over the month but was down by 0.4 percentage point over the year. (See table A-1.)

The number of people employed part time for economic reasons, at 4.7 million, changed little in July. These individuals would have preferred full-time employment but were working part time because their hours had been reduced or they were unable to find full-time jobs. (See table A-8.)

The number of people not in the labor force who currently want a job changed little in July at 6.2 million but was up by 568,000 over the year. These individuals were not counted as unemployed because they were not actively looking for work during the 4 weeks preceding the survey or were unavailable to take a job. (See table A-1.)

Among those not in the labor force who wanted a job, the number of people marginally attached to the labor force changed little at 1.7 million in July. These individuals wanted and were available for work and had looked for a job sometime in the prior 12 months but had not looked for work in the 4 weeks preceding the survey. The number of discouraged workers decreased by 212,000 in July to 425,000, largely offsetting an increase in the prior month. Discouraged workers are a subset of the marginally attached who believed that no jobs were available for them. (See Summary table A.)

Establishment Survey Data

Total nonfarm payroll employment changed little in July (+73,000) and has shown little change since April. Over the month, employment continued to trend up in health care and in social assistance. Federal government continued to lose jobs. (See table B-1.)

In July, health care added 55,000 jobs, above the average monthly gain of 42,000 over the prior 12 months. Over the month, job gains occurred in ambulatory health care services (+34,000) and hospitals (+16,000).

Social assistance employment continued to trend up in July (+18,000), reflecting continued job growth in individual and family services (+21,000).

Federal government employment continued to decline in July (-12,000) and is down by 84,000 since reaching a peak in January. (Employees on paid leave or receiving ongoing severance pay are counted as employed in the establishment survey.)

Employment showed little change over the month in other major industries, including mining, quarrying, and oil and gas extraction; construction; manufacturing; wholesale trade; retail trade; transportation and warehousing; information; financial activities; professional and business services; leisure and hospitality; and other services.

Average hourly earnings for all employees on private nonfarm payrolls rose by 12 cents, or 0.3 percent, to $36.44 in July. Over the past 12 months, average hourly earnings have increased by 3.9 percent. In July, average hourly earnings of private-sector production and nonsupervisory employees rose by 8 cents, or 0.3 percent, to $31.34. (See tables B-3 and B-8.)

The average workweek for all employees on private nonfarm payrolls edged up by 0.1 hour to 34.3 hours in July. In manufacturing, the average workweek held at 40.1 hours, and overtime edged down to 2.8 hours. The average workweek for production and nonsupervisory employees on private nonfarm payrolls edged up by 0.1 hour to 33.7 hours in July. (See tables B-2 and B-7.)

Revisions for May and June were larger than normal. The change in total nonfarm payroll employment for May was revised down by 125,000, from +144,000 to +19,000, and the change for June was revised down by 133,000, from +147,000 to +14,000. With these revisions, employment in May and June combined is 258,000 lower than previously reported. (Monthly revisions result from additional reports received from businesses and government agencies since the last published estimates andfrom the recalculation of seasonal factors.)

The Employment Situation for August is scheduled to be released on Friday, September 5, 2025, at 8:30 a.m. (ET).

Employment Situation Summary Table A. Household data, seasonally adjusted - 2025 M07 Results

Category July 2024 May 2025 June 2025 July 2025 Change from: June 2025-July 2025
Employment status          
Civilian noninstitutional population 268,644 273,385 273,585 273,785 200
Civilian labor force 168,315 170,510 170,380 170,342 -38
Participation rate 62.7 62.4 62.3 62.2 -0.1
Employed 161,219 163,273 163,366 163,106 -260
Unemployed 7,097 7,237 7,015 7,236 221
Unemployment rate 4.2 4.2 4.1 4.2 0.1
Not in labor force 100,329 102,875 103,204 103,443 239
Unemployment rates          
Total, 16 years and over 4.2 4.2 4.1 4.2 0.1
Adult men (20 years and over) 4.0 3.9 3.9 4.0 0.1
Adult women (20 years and over) 3.8 3.9 3.6 3.7 0.1
Teenagers (16 to 19 years) 12.6 13.4 14.4 15.2 0.8
White 3.8 3.8 3.6 3.7 0.1
Black or African American 6.3 6.0 6.8 7.2 0.4
Asian 3.7 3.6 3.5 3.9 0.4
Hispanic or Latino ethnicity 5.3 5.1 4.8 5.0 0.2
Total, 25 years and over 3.5 3.4 3.3 3.4 0.1
Some college or associate degree 3.5 3.3 3.2 3.0 -0.2
Bachelor’s degree and higher 2.3 2.6 2.5 2.7 0.2
Reason for unemployment          
Job losers and people who completed temporary jobs 3,545 3,457 3,293 3,405 112
Job leavers 855 704 825 784 -41
Reentrants 2,161 2,288 2,145 2,180 35
New entrants 648 725 710 985 275
Duration of unemployment          
Less than 5 weeks 2,348 2,451 2,241 2,299 58
5 to 14 weeks 2,162 2,208 2,131 2,034 -97
15 to 26 weeks 1,078 1,039 1,063 1,167 104
27 weeks and over 1,543 1,457 1,647 1,826 179
Employed people at work part time          
Part time for economic reasons 4,564 4,624 4,465 4,684 219
Slack work or business conditions 3,001 3,007 3,109 3,035 -74
Could only find part-time work 1,195 1,385 1,161 1,264 103
Part time for noneconomic reasons 22,048 22,588 22,556 22,770 214
People not in the labor force          
Marginally attached to the labor force 1,571 1,556 1,790 1,689 -101
Discouraged workers 408 381 637 425 -212

NOTE: People whose ethnicity is identified as Hispanic or Latino may be of any race. Detail for the seasonally adjusted data shown in this table will not necessarily add to totals because of the independent seasonal adjustment of the various series. Updated population controls are introduced annually with the release of January data.

Employment Situation Technical Note - 2025 M07 Results

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 121,000 businesses and government agencies, representing approximately 631,000 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 jobs.

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 active efforts to find employment sometime during the 4-week period ending with the reference week. People 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 the employed and unemployed. Those people 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 worked or received pay for any part of the reference pay period, including people on paid leave. People 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 2022 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. Percentage distributions of unemployment by reason and duration are derived from the sum of the independently seasonally adjusted component series and will not necessarily match calculations made using the seasonally adjusted total unemployment level. Additional information about seasonal adjustment in the household survey can be found at

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 136,000. 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 -86,000 to +186,000 (50,000 +/- 136,000). 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. Benchmarks also incorporate changes in the classification of industries when necessary. Over the past decade, absolute benchmark revisions for total nonfarm employment have averaged 0.1 percent, with a range from -0.3 percent to 0.3 percent.

Other information

If you are deaf, hard of hearing, or have a speech disability, please dial 7-1-1 to access telecommunications relay services. Revisions for May and June were larger than normal. The change in total nonfarm payroll employment for May was revised down by 125,000, from +144,000 to +19,000, and the change for June was revised down by 133,000, from +147,000 to +14,000. With these revisions, employment in May and June combined is 258,000 lower than previously reported. (Monthly revisions result from additional reports received from businesses and government agencies since the last published estimates andfrom the recalculation of seasonal factors.)

The Employment Situation for August is scheduled to be released on Friday, September 5, 2025, at 8:30 a.m. (ET).

Employment Situation Summary Table A. Household data, seasonally adjusted - 2025 M07 Results

Category July 2024 May 2025 June 2025 July 2025 Change from: June 2025-July 2025
Employment status          
Civilian noninstitutional population 268,644 273,385 273,585 273,785 200
Civilian labor force 168,315 170,510 170,380 170,342 -38
Participation rate 62.7 62.4 62.3 62.2 -0.1
Employed 161,219 163,273 163,366 163,106 -260
Unemployed 7,097 7,237 7,015 7,236 221
Unemployment rate 4.2 4.2 4.1 4.2 0.1
Not in labor force 100,329 102,875 103,204 103,443 239
Unemployment rates          
Total, 16 years and over 4.2 4.2 4.1 4.2 0.1
Adult men (20 years and over) 4.0 3.9 3.9 4.0 0.1
Adult women (20 years and over) 3.8 3.9 3.6 3.7 0.1
Teenagers (16 to 19 years) 12.6 13.4 14.4 15.2 0.8
White 3.8 3.8 3.6 3.7 0.1
Black or African American 6.3 6.0 6.8 7.2 0.4
Asian 3.7 3.6 3.5 3.9 0.4
Hispanic or Latino ethnicity 5.3 5.1 4.8 5.0 0.2
Total, 25 years and over 3.5 3.4 3.3 3.4 0.1
Some college or associate degree 3.5 3.3 3.2 3.0 -0.2
Bachelor’s degree and higher 2.3 2.6 2.5 2.7 0.2
Reason for unemployment          
Job losers and people who completed temporary jobs 3,545 3,457 3,293 3,405 112
Job leavers 855 704 825 784 -41
Reentrants 2,161 2,288 2,145 2,180 35
New entrants 648 725 710 985 275
Duration of unemployment          
Less than 5 weeks 2,348 2,451 2,241 2,299 58
5 to 14 weeks 2,162 2,208 2,131 2,034 -97
15 to 26 weeks 1,078 1,039 1,063 1,167 104
27 weeks and over 1,543 1,457 1,647 1,826 179
Employed people at work part time          
Part time for economic reasons 4,564 4,624 4,465 4,684 219
Slack work or business conditions 3,001 3,007 3,109 3,035 -74
Could only find part-time work 1,195 1,385 1,161 1,264 103
Part time for noneconomic reasons 22,048 22,588 22,556 22,770 214
People not in the labor force          
Marginally attached to the labor force 1,571 1,556 1,790 1,689 -101
Discouraged workers 408 381 637 425 -212

NOTE: People whose ethnicity is identified as Hispanic or Latino may be of any race. Detail for the seasonally adjusted data shown in this table will not necessarily add to totals because of the independent seasonal adjustment of the various series. Updated population controls are introduced annually with the release of January data.

Employment Situation Technical Note - 2025 M07 Results

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 121,000 businesses and government agencies, representing approximately 631,000 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 jobs.

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 active efforts to find employment sometime during the 4-week period ending with the reference week. People 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 the employed and unemployed. Those people 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 worked or received pay for any part of the reference pay period, including people on paid leave. People 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 2022 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. Percentage distributions of unemployment by reason and duration are derived from the sum of the independently seasonally adjusted component series and will not necessarily match calculations made using the seasonally adjusted total unemployment level. Additional information about seasonal adjustment in the household survey can be found at

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 136,000. 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 -86,000 to +186,000 (50,000 +/- 136,000). 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. Benchmarks also incorporate changes in the classification of industries when necessary. Over the past decade, absolute benchmark revisions for total nonfarm employment have averaged 0.1 percent, with a range from -0.3 percent to 0.3 percent.

Other information

If you are deaf, hard of hearing, or have a speech disability, please dial 7-1-1 to access telecommunications relay services.

Employment Situation Summary Table A. Household data, seasonally adjusted - 2025 M07 Results

Category July 2024 May 2025 June 2025 July 2025 Change from: June 2025-July 2025
Employment status          
Civilian noninstitutional population 268,644 273,385 273,585 273,785 200
Civilian labor force 168,315 170,510 170,380 170,342 -38
Participation rate 62.7 62.4 62.3 62.2 -0.1
Employed 161,219 163,273 163,366 163,106 -260
Unemployed 7,097 7,237 7,015 7,236 221
Unemployment rate 4.2 4.2 4.1 4.2 0.1
Not in labor force 100,329 102,875 103,204 103,443 239
Unemployment rates          
Total, 16 years and over 4.2 4.2 4.1 4.2 0.1
Adult men (20 years and over) 4.0 3.9 3.9 4.0 0.1
Adult women (20 years and over) 3.8 3.9 3.6 3.7 0.1
Teenagers (16 to 19 years) 12.6 13.4 14.4 15.2 0.8
White 3.8 3.8 3.6 3.7 0.1
Black or African American 6.3 6.0 6.8 7.2 0.4
Asian 3.7 3.6 3.5 3.9 0.4
Hispanic or Latino ethnicity 5.3 5.1 4.8 5.0 0.2
Total, 25 years and over 3.5 3.4 3.3 3.4 0.1
Some college or associate degree 3.5 3.3 3.2 3.0 -0.2
Bachelor’s degree and higher 2.3 2.6 2.5 2.7 0.2
Reason for unemployment          
Job losers and people who completed temporary jobs 3,545 3,457 3,293 3,405 112
Job leavers 855 704 825 784 -41
Reentrants 2,161 2,288 2,145 2,180 35
New entrants 648 725 710 985 275
Duration of unemployment          
Less than 5 weeks 2,348 2,451 2,241 2,299 58
5 to 14 weeks 2,162 2,208 2,131 2,034 -97
15 to 26 weeks 1,078 1,039 1,063 1,167 104
27 weeks and over 1,543 1,457 1,647 1,826 179
Employed people at work part time          
Part time for economic reasons 4,564 4,624 4,465 4,684 219
Slack work or business conditions 3,001 3,007 3,109 3,035 -74
Could only find part-time work 1,195 1,385 1,161 1,264 103
Part time for noneconomic reasons 22,048 22,588 22,556 22,770 214
People not in the labor force          
Marginally attached to the labor force 1,571 1,556 1,790 1,689 -101
Discouraged workers 408 381 637 425 -212

NOTE: People whose ethnicity is identified as Hispanic or Latino may be of any race. Detail for the seasonally adjusted data shown in this table will not necessarily add to totals because of the independent seasonal adjustment of the various series. Updated population controls are introduced annually with the release of January data.

Employment Situation Technical Note - 2025 M07 Results

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 121,000 businesses and government agencies, representing approximately 631,000 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 jobs.

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 active efforts to find employment sometime during the 4-week period ending with the reference week. People 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 the employed and unemployed. Those people 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 worked or received pay for any part of the reference pay period, including people on paid leave. People 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 2022 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. Percentage distributions of unemployment by reason and duration are derived from the sum of the independently seasonally adjusted component series and will not necessarily match calculations made using the seasonally adjusted total unemployment level. Additional information about seasonal adjustment in the household survey can be found at

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 136,000. 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 -86,000 to +186,000 (50,000 +/- 136,000). 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. Benchmarks also incorporate changes in the classification of industries when necessary. Over the past decade, absolute benchmark revisions for total nonfarm employment have averaged 0.1 percent, with a range from -0.3 percent to 0.3 percent.

Other information

If you are deaf, hard of hearing, or have a speech disability, please dial 7-1-1 to access telecommunications relay services. at 8:30 a.m. (ET).

Employment Situation Summary Table A. Household data, seasonally adjusted - 2025 M07 Results

Category July 2024 May 2025 June 2025 July 2025 Change from: June 2025-July 2025
Employment status          
Civilian noninstitutional population 268,644 273,385 273,585 273,785 200
Civilian labor force 168,315 170,510 170,380 170,342 -38
Participation rate 62.7 62.4 62.3 62.2 -0.1
Employed 161,219 163,273 163,366 163,106 -260
Unemployed 7,097 7,237 7,015 7,236 221
Unemployment rate 4.2 4.2 4.1 4.2 0.1
Not in labor force 100,329 102,875 103,204 103,443 239
Unemployment rates          
Total, 16 years and over 4.2 4.2 4.1 4.2 0.1
Adult men (20 years and over) 4.0 3.9 3.9 4.0 0.1
Adult women (20 years and over) 3.8 3.9 3.6 3.7 0.1
Teenagers (16 to 19 years) 12.6 13.4 14.4 15.2 0.8
White 3.8 3.8 3.6 3.7 0.1
Black or African American 6.3 6.0 6.8 7.2 0.4
Asian 3.7 3.6 3.5 3.9 0.4
Hispanic or Latino ethnicity 5.3 5.1 4.8 5.0 0.2
Total, 25 years and over 3.5 3.4 3.3 3.4 0.1
Some college or associate degree 3.5 3.3 3.2 3.0 -0.2
Bachelor’s degree and higher 2.3 2.6 2.5 2.7 0.2
Reason for unemployment          
Job losers and people who completed temporary jobs 3,545 3,457 3,293 3,405 112
Job leavers 855 704 825 784 -41
Reentrants 2,161 2,288 2,145 2,180 35
New entrants 648 725 710 985 275
Duration of unemployment          
Less than 5 weeks 2,348 2,451 2,241 2,299 58
5 to 14 weeks 2,162 2,208 2,131 2,034 -97
15 to 26 weeks 1,078 1,039 1,063 1,167 104
27 weeks and over 1,543 1,457 1,647 1,826 179
Employed people at work part time          
Part time for economic reasons 4,564 4,624 4,465 4,684 219
Slack work or business conditions 3,001 3,007 3,109 3,035 -74
Could only find part-time work 1,195 1,385 1,161 1,264 103
Part time for noneconomic reasons 22,048 22,588 22,556 22,770 214
People not in the labor force          
Marginally attached to the labor force 1,571 1,556 1,790 1,689 -101
Discouraged workers 408 381 637 425 -212

NOTE: People whose ethnicity is identified as Hispanic or Latino may be of any race. Detail for the seasonally adjusted data shown in this table will not necessarily add to totals because of the independent seasonal adjustment of the various series. Updated population controls are introduced annually with the release of January data.

Employment Situation Technical Note - 2025 M07 Results

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 121,000 businesses and government agencies, representing approximately 631,000 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 jobs.

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 active efforts to find employment sometime during the 4-week period ending with the reference week. People 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 the employed and unemployed. Those people 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 worked or received pay for any part of the reference pay period, including people on paid leave. People 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 2022 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. Percentage distributions of unemployment by reason and duration are derived from the sum of the independently seasonally adjusted component series and will not necessarily match calculations made using the seasonally adjusted total unemployment level. Additional information about seasonal adjustment in the household survey can be found at

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 136,000. 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 -86,000 to +186,000 (50,000 +/- 136,000). 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. Benchmarks also incorporate changes in the classification of industries when necessary. Over the past decade, absolute benchmark revisions for total nonfarm employment have averaged 0.1 percent, with a range from -0.3 percent to 0.3 percent.

Other information

If you are deaf, hard of hearing, or have a speech disability, please dial 7-1-1 to access telecommunications relay services.

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