BLS U S Bureau of Labor Statistics : Usual Weekly Earnings of Wage and Salary Workers

For release 10:00 a.m. (EST) Thursday, January 17, 2019

USDL-19-0077

Technical information: [phone] •[e-mail]• www.bls.gov/cps Media contact: [phone] •[e-mail]

USUAL WEEKLY EARNINGS OF WAGE AND SALARY WORKERS

FOURTH QUARTER 2018

Median weekly earnings of the nation's 115.9 million full-time wage and salary workers were $900 in the fourth quarter of 2018 (not seasonally adjusted), the U.S. Bureau of Labor Statistics reported today. This was 5.0 percent higher than a year earlier, compared with a gain of 2.2 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 fourth-quarter data:

• • Median weekly earnings of full-time workers were $900 in the fourth quarter of 2018. Women had median weekly earnings of $794, or 80.0 percent of the $993 median for men. (See table 2.)

• • The women's-to-men's earnings ratio varied by race and ethnicity. White women earned 79.7 percent as much as their male counterparts, compared with 86.0 percent for Black women, 74.6 percent for Asian women, and 82.9 percent for Hispanic women. (See table 2.)

• • Among the major race and ethnicity groups, median weekly earnings of Blacks ($712) and Hispanics ($684) working at full-time jobs were lower than those of Whites ($931) and Asians ($1,095). By sex, median weekly earnings for Black men were $773, or 75.5 percent of the median for White men ($1,024). Median earnings for Hispanic men were $736, or 71.9 percent of the median for White men. The difference was less among women, as Black women's median earnings were $665, or 81.5 percent of those for White women ($816), and earnings for Hispanic women were $610, or 74.8 percent of those for White women. Earnings of Asian men ($1,256) and women ($937) were higher than those of their White counterparts. (See table 2.)

• • By age, median weekly earnings were highest for men ages 55 to 64 at $1,191. Usual weekly earnings were highest for women ages 35 to 64: median weekly earnings were $877 for women ages 35 to 44, $876 for women ages 45 to 54, and $895 for women ages 55 to 64. Men and women ages 16 to 24 had the lowest median weekly earnings, $609 and $539, respectively. (See table 3.)

• • Among the major occupational groups, persons employed full time in management, professional, and related occupations had the highest median weekly earnings-$1,505 for men and $1,102 for women. Men and women employed in service jobs earned the least, $675 and $512, respectively. (See table 4.)

• • By educational attainment, full-time workers age 25 and over without a high school diploma had median weekly earnings of $543, compared with $746 for high school graduates (no college) and $1,340 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 $3,909 or more per week, compared with $2,884 or more for their female counterparts. (See table 5.)

• • Seasonally adjusted median weekly earnings were $897 in the fourth quarter of 2018, little changed from the previous quarter ($893). (See table 1.)

Annual Averages for 2017 and 2018

In addition to the data for the fourth quarter, this news release includes 2017 and 2018 annual averages on median weekly earnings for major demographic and occupational groups, and 2018 annual average data for educational attainment groups. (See tables 7, 8, and 9.) Annual average data on median usual weekly earnings for men and women by detailed occupational categories will be posted online atwww.bls.gov/cps/tables.htm#weekearnwhen they become available.

Revision of Seasonally Adjusted Usual Weekly Earnings Data

Seasonally adjusted median usual weekly earnings data shown in table 1 of this news release have been revised using updated seasonal adjustment factors from the Current Population Survey, a procedure done at the end of each calendar year. The revisions directly affected the number of full-time wage and salary workers and current dollar estimates of median weekly earnings; estimates of constant (1982-84) dollar median weekly earnings were indirectly affected. Seasonally adjusted estimates back to the first quarter of 2014 were subject to revision.

The Usual Weekly Earnings news release for the first quarter of 2019, scheduled for release on April 16, 2019, will incorporate revisions to the seasonally adjusted data for the median weekly earnings in constant (1982-84) dollars. Seasonally adjusted constant (1982-84) dollar estimates back to the first quarter of 2014 will be subject to revision due to annual revisions to seasonally adjusted data for the Consumer Price Index for All Urban Consumers (CPI-U).

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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.

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: [phone]; Federal Relay Service: [phone].

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 atwww.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 atwww.bls.gov/cps/documentation.htm#sa.

Table 1. Median usual weekly earnings of full-time wage and salary workers by sex, quarterly averages, seasonally adjusted

Number of workers

(in thousands)Median weekly earningsYear and quarter

In current dollars

In constant (1982-84) dollars

Total	Men	Women	Total	Men	Women	Total	Men	Women
$	$	$	$	$	$
2009
4th quarter .........................................	98,555	54,410	44,145	747	823	666	344	379	307
2010
1st quarter .........................................	98,143	54,098	44,045	748	836	662	344	384	304
2nd quarter ........................................	99,605	55,028	44,577	742	814	671	342	374	309
3rd quarter .........................................	100,412	55,620	44,792	746	821	670	342	377	308
4th quarter .........................................	99,958	55,486	44,472	750	826	676	341	376	308
2011
1st quarter .........................................	99,670	55,337	44,333	750	821	679	338	370	306
2nd quarter ........................................	100,347	55,821	44,526	754	830	687	336	370	306
3rd quarter .........................................	100,495	56,046	44,449	760	836	681	336	370	301
4th quarter .........................................	101,337	56,687	44,650	760	838	686	335	369	302
2012
1st quarter .........................................	102,161	57,110	45,051	764	841	693	335	368	303
2nd quarter ........................................	102,525	57,079	45,447	772	870	687	337	380	300
3rd quarter .........................................	102,587	57,207	45,380	766	836	693	333	364	302
4th quarter .........................................	103,748	57,772	45,977	771	868	690	333	375	298
2013
1st quarter .........................................	103,928	57,884	46,044	768	860	699	331	370	301
2nd quarter ........................................	103,988	57,944	46,044	777	863	706	335	372	304
3rd quarter .........................................	104,400	58,082	46,318	779	855	705	334	367	302
4th quarter .........................................	104,764	58,095	46,669	782	865	712	334	369	304
2014
1st quarter .........................................	105,633	58,682	46,951	790	865	716	335	367	304
2nd quarter ........................................	106,342	59,486	46,855	781	860	715	330	363	302
3rd quarter .........................................	106,726	59,543	47,183	798	878	721	336	370	304
4th quarter .........................................	107,436	60,123	47,313	795	878	724	336	371	306
2015
1st quarter .........................................	108,486	60,364	48,122	801	886	724	341	377	307
2nd quarter ........................................	108,544	60,400	48,144	803	890	726	339	376	306
3rd quarter .........................................	109,269	60,977	48,292	810	896	727	341	377	306
4th quarter .........................................	110,049	61,273	48,776	822	904	730	345	380	307
2016
1st quarter .........................................	110,427	61,627	48,799	823	903	743	346	380	312
2nd quarter ........................................	110,929	61,787	49,142	827	914	744	345	382	311
3rd quarter .........................................	111,566	62,082	49,483	833	917	750	346	381	312
4th quarter .........................................	111,463	62,249	49,214	846	924	760	349	382	314
2017
1st quarter .........................................	111,978	62,462	49,516	857	940	759	351	385	311
2nd quarter ........................................	113,118	62,942	50,176	862	939	780	353	385	320
3rd quarter .........................................	113,623	63,155	50,468	865	943	771	353	385	314
4th quarter .........................................	114,372	63,377	50,996	854	943	771	345	381	312
2018
1st quarter .........................................	114,678	64,007	50,671	874	955	776	350	383	311
2nd quarter ........................................	115,481	64,136	51,345	880	964	780	351	385	312
3rd quarter .........................................	115,945	64,198	51,747	893	980	801	355	389	318
4th quarter .........................................	116,160	64,237	51,923	897	991	796	355	392	315

NOTE: Updated population controls are introduced annually with the release of January data.