For release 10:00 a.m. (ET) Friday, April 16, 2021 			USDL-21-0655

Technical information:	cpsinfo@bls.gov  *  www.bls.gov/cps
Media contact:	        (202) 691-5902  *  PressOffice@bls.gov


                USUAL WEEKLY EARNINGS OF WAGE AND SALARY WORKERS
                               FIRST QUARTER 2021


Median weekly earnings of the nation's 112.1 million full-time wage and salary
workers were $989 in the first quarter of 2021 (not seasonally adjusted), the
U.S. Bureau of Labor Statistics reported today. This was 3.3 percent higher
than a year earlier, compared with a gain of 1.9 percent in the Consumer 
Price Index for All Urban Consumers (CPI-U) over the same period.

Data on usual weekly earnings are collected as part of the Current Population
Survey, a nationwide sample survey of households in which respondents are asked,
among other things, how much each wage and salary worker usually earns. (See
the Technical Note in this news release.) Data shown in this news release are
not seasonally adjusted unless otherwise specified.

Highlights from the first-quarter data:

 --Median weekly earnings of full-time workers were $989 in the first quarter of
   2021. Women had median weekly earnings of $900, 82.6 percent of the $1,089
   median for men. (See table 2.) 

 --The women's-to-men's earnings ratio varied by race and ethnicity. White women
   earned 81.6 percent as much as their male counterparts, compared with 92.1
   percent for Black women, 80.5 percent for Asian women, and 88.3 percent for 
   Hispanic women. (See table 2.)

 --Among the major race and ethnicity groups, median weekly earnings for Blacks
   ($799) and Hispanics ($750) working full-time jobs were lower than those of
   Whites ($1,006) and Asians ($1,286). By sex, median weekly earnings for Black
   men were $834, or 74.6 percent of the median for White men ($1,118). Median
   earnings for Hispanic men were $788, or 70.5 percent of the median for White
   men. The difference was less among women, as Black women's median earnings
   were $768, or 84.2 percent of those for White women ($912), and earnings for
   Hispanic women were $696, or 76.3 percent of those for White women. Earnings
   for Asian men ($1,408) and women ($1,134) were higher than those of their
   White counterparts. (See table 2.)

 --By age, median weekly earnings were highest for men ages 45 to 54 ($1,334).
   Usual weekly earnings were highest for women ages 35 to 64: median weekly
   earnings were $999 for women ages 35 to 44, $1,002 for women ages 45 to 54,
   and $964 for women ages 55 to 64. Men and women ages 16 to 24 had the lowest 
   median weekly earnings, $634 and $593, respectively. Men's and women's
   earnings were closer among younger workers than older workers; for example,
   women ages 16 to 24 earned 93.5 percent as much as men in the same age group,
   while the women's-to-men's earnings ratio was 79.9 percent for those age 55
   and over. (See table 3.) 

 --Among the major occupational groups, persons employed full time in management,
   professional, and related occupations had the highest median weekly earnings--
   $1,615 for men and $1,179 for women. Men and women employed in service 
   occupations earned the least, $741 and $582, respectively. (See table 4.) 

 --By educational attainment, full-time workers age 25 and over without a high
   school diploma had median weekly earnings of $613, compared with $792 for high
   school graduates (no college) and $1,426 for those holding at least a bachelor's
   degree. Among college graduates with advanced degrees (master's, professional,
   and doctoral degrees), the highest earning 10 percent of male workers made
   $4,355 or more per week, compared with $2,907 or more for their female 
   counterparts. (See table 5.) 

 --Seasonally adjusted median weekly earnings were $984 in the first quarter of
   2021, essentially unchanged from the previous quarter. (See table 1.)


 _________________________________________________________________________________
|										  |
|                    Coronavirus (COVID-19) Pandemic Impact on                    |
|                           Usual Weekly Earnings Data				  |
|										  |
| Usual weekly earnings data for the first quarter of 2021 continue to reflect	  |
| the impact on the labor market of the coronavirus (COVID-19) pandemic and 	  |
| efforts to contain it. More information on labor market developments in 	  |
| recent months is available at 						  |
| www.bls.gov/covid19/effects-of-covid-19-pandemic-and-response-on-the-		  |
| employment-situation-news-release.htm. 					  |
|_________________________________________________________________________________|


 _________________________________________________________________________________
|										  |
|           Revision of Seasonally Adjusted Usual Weekly Earnings Data            |
|										  |
| Seasonally adjusted data for median usual weekly earnings in constant (1982-84) |
| dollars have been updated using revised seasonally adjusted data for the 	  |
| Consumer Price Index for All Urban Consumers (CPI-U). (Data are shown in table  |
| 1 of this news release.) Seasonally adjusted constant (1982-84) dollar 	  |
| estimates back to the first quarter of 2016 were subject to revision.		  |
|_________________________________________________________________________________|

Technical Note


   The estimates in this release were obtained from the Current Population Survey (CPS),
which provides basic information on the labor force, employment, and unemployment. The
survey is conducted monthly for the Bureau of Labor Statistics (BLS) by the U.S. Census
Bureau using a scientifically selected national sample of about 60,000 eligible house-
holds, with coverage in all 50 states and the District of Columbia. The earnings data
are collected from one-fourth of the CPS monthly sample and are limited to wage and
salary workers. All self-employed workers, both incorporated and unincorporated, are
excluded from CPS earnings estimates.

   Material in this news release is in the public domain and may be used without
permission. This information is available to sensory impaired individuals upon
request. Voice telephone: (202) 691-5200; Federal Relay Service: (800) 877-8339.

Definitions

   The principal definitions used in connection with the earnings data in this news
release are described briefly below.

   Usual weekly earnings. Data represent earnings before taxes and other deductions and
include any overtime pay, commissions, or tips usually received (at the main job in the
case of multiple jobholders). Prior to 1994, respondents were asked how much they
usually earned per week. Since January 1994, respondents have been asked to identify
the easiest way for them to report earnings (hourly, weekly, biweekly, twice monthly,
monthly, annually, or other) and how much they usually earn in the reported time period.

   Earnings reported on a basis other than weekly are converted to a weekly equivalent.
The term "usual" is determined by each respondent's own understanding of the term. If
the respondent asks for a definition of "usual," interviewers are instructed to define
the term as more than half the weeks worked during the past 4 or 5 months.

   Medians (and other quantiles) of weekly earnings. The median (or upper limit of the
second quartile) is the midpoint in a given earnings distribution, with half of workers
having earnings above the median and the other half having earnings below the median.
Ten percent of a given distribution have earnings below the upper limit of the first
decile (90 percent have higher earnings), 25 percent have earnings below the upper limit
of the first quartile (75 percent have higher earnings), 75 percent have earnings below
the upper limit of the third quartile (25 percent have higher earnings), and 90 percent
have earnings below the upper limit of the ninth decile (10 percent have higher earnings).

   The BLS procedure for estimating the median of an earnings distribution places each 
reported or calculated weekly earnings value into a $50-wide interval that is centered
around a multiple of $50. The median is calculated through the linear interpolation of 
the interval in which the median lies.

   Changes over time in the medians (and other quantile boundaries) for specific groups
may not necessarily be consistent with the movements estimated for the overall quantile
boundary. The most common reasons for this possible anomaly are as follows: (1) there
could be a change in the relative weights of the subgroups. For example, the median of
16- to 24-year-olds and the median earnings of those 25 years and over may rise, but if
the lower earning 16-to-24 age group accounts for a greatly increased share of the
total, the overall median could actually fall. (2) there could be a large change in the
shape of the distribution of reported earnings, particularly near a quantile boundary.
This change could be caused by survey observations that are clustered at rounded values,
such as $400 or $500. An estimate lying in a $50-wide centered interval containing such
a cluster or "spike" tends to change more slowly than one in other intervals.

   Constant dollars. The Consumer Price Index for All Urban Consumers (CPI-U) is used
to convert current dollars to constant (1982-84) dollars.

   Wage and salary workers. These are workers who receive wages, salaries, commissions,
tips, payment in kind, or piece rates. The group includes employees in both the private
and public sectors but, for the purposes of the earnings series, it excludes all self-
employed persons, both those with incorporated businesses and those with unincorporated
businesses.

   Full-time workers. For the purpose of producing estimates of earnings, workers who
usually work 35 hours or more per week at their sole or principal job are defined as
working full time.

   Part-time workers. For the purpose of producing estimates of earnings, workers who
usually work fewer than 35 hours per week at their sole or principal job are defined as
working part time.

   Race. In the survey process, race is determined by the household respondent. In
accordance with the Office of Management and Budget guidelines, White, Black or African
American, Asian, American Indian or Alaska Native, and Native Hawaiian or Other Pacific 
Islander are terms used to describe a person's race. Estimates for the latter two race
groups and persons who selected more than one race are not included in this release due
to insufficient sample size.

   Hispanic or Latino ethnicity. This refers to people who identified themselves in the
survey process as being of Hispanic, Latino, or Spanish origin. People whose ethnicity
is identified as Hispanic or Latino may be of any race.

Reliability

   Statistics based on the CPS 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. 

   The CPS data also are affected by nonsampling error. Nonsampling error 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, and errors made in the collection or
processing of the data.

   Additional information about the reliability of data from the CPS is available on the
BLS website at www.bls.gov/cps/documentation.htm#reliability.

Seasonal adjustment

   Over the course of a year, the size of the nation's labor force and other measures
of labor market activity undergo regularly occurring fluctuations. These recurring
events include seasonal changes in weather, major holidays, and the opening and closing
of schools. The effect of such seasonal variations can be very large.

   Because 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 easier to spot. The
seasonally adjusted figures provide a more useful tool with which to analyze changes
in quarter-to-quarter activity.

   At the end of each calendar year, the seasonally adjusted data are revised for the past
5 years when the seasonal adjustment factors are updated. More information on seasonal
adjustment is available on the BLS website at www.bls.gov/cps/documentation.htm#sa.