Usual Weekly Earnings of Wage and Salary Workers News Release

For release 10:00 a.m. (ET) Tuesday, April 18, 2023 			       USDL-23-0722

Technical information: (202) 691-6378  •  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 2023


Median weekly earnings of the nation's 119.2 million full-time wage and salary workers
were $1,100 in the first quarter of 2023 (not seasonally adjusted), the U.S. Bureau
of Labor Statistics reported today. This was 6.1 percent higher than a year earlier,
compared with a gain of 5.8 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 $1,100 in the first quarter of
   2023. Women had median weekly earnings of $996, or 84.0 percent of the $1,186
   median for men. (See table 2.)

 --The women's-to-men's earnings ratio varied by race and ethnicity. White women
   earned 82.4 percent as much as their male counterparts, compared with 94.8 percent
   for Black women, 83.5 percent for Asian women, and 85.0 percent for Hispanic women.
   (See table 2.)

 --Among the major race and ethnicity groups, median weekly earnings of Blacks ($886)
   and Hispanics ($868) working full-time jobs were lower than those of Whites ($1,130)
   and Asians ($1,468). By sex, median weekly earnings for Black men were $909, or
   74.4 percent of the median for White men ($1,222). Median earnings for Hispanic
   men were $917, or 75.0 percent of the median for White men. The difference was 
   less among women, as Black women's median earnings were $862, or 85.6 percent of
   those for White women ($1,007), and earnings for Hispanic women were $779, or 77.4
   percent of those for White women. Earnings of Asian men ($1,573) and women ($1,313)
   were higher than those of their White counterparts. (See table 2.)

 --By age, usual weekly earnings were highest for men ages 35 to 64: median weekly
   earnings were $1,329 for men ages 35 to 44, $1,389 for men ages 45 to 54, and
   $1,393 for men ages 55 to 64. Among women, usual weekly earnings were also highest
   for workers ages 35 to 64: median weekly earnings were $1,112 for women ages 35
   to 44, $1,098 for women ages 45 to 54, and $1,044 for women ages 55 to 64. Men
   and women ages 16 to 24 had the lowest median weekly earnings, $751 and $690,
   respectively. Men's and women's earnings were closer among younger workers than
   older workers; for example, women ages 16 to 24 earned 91.9 percent as much as men
   in the same age group, while the women's-to-men's earnings ratio was 75.1 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--
   $1,775 for men and $1,344 for women. Men employed in service occupations earned
   the least at $793. Women who worked in service occupations ($662); natural resources,
   construction, and maintenance occupations ($664); and production, transportation,
   and material moving occupations ($688) earned the least. (See table 4.)

 --By educational attainment, full-time workers age 25 and over without a high school
   diploma had median weekly earnings of $682, compared with $884 for high school
   graduates (no college) and $1,621 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 $5,007 or more per
   week, compared with $3,426 or more for their female counterparts. (See table 5.)

 --Seasonally adjusted median weekly earnings were $1,095 in the first quarter of 
   2023, little changed from the previous quarter ($1,084). (See table 1.)


 ____________________________________________________________________________________
|										     |
|             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 2018 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 
households, 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.

   If you are deaf, hard of hearing, or have a speech disability, please dial 7-1-1 to
access telecommunications relay services or the information voice phone at: 
(202) 691-5200. This news release is in the public domain and may be reproduced 
without permission.

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.