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.