Statistics and Time Series.

Real Earnings: Bureau of Labor Statistics, January 2016.

Press Release by the Bureau of Labor Statistics.

All employees Real average hourly earnings for all employees increased 0.4 percent from December to January, seasonally adjusted, the U.S. Bureau of Labor Statistics reported today. This result stems from a 0.5-percent increase in average hourly earnings combined with no change in the Consumer Price Index for All Urban Consumers (CPI-U).

Real average weekly earnings increased 0.7 percent over the month due to the increase in real average hourly earnings combined with a 0.3-percent increase in the average workweek.

Real average hourly earnings increased 1.1 percent, seasonally adjusted, from January 2015 to January 2016. This increase in real average hourly earnings combined with no change in the average workweek resulted in a 1.2-percent increase in real average weekly earnings over this period.

Production and nonsupervisory employees.

Real average hourly earnings for production and nonsupervisory employees increased 0.3 percent from December to January, seasonally adjusted. This result stems from a 0.3-percent increase in average hourly earnings combined with no change in the Consumer Price Index for Urban Wage Earners and Clerical Workers (CPI-W).

Real average weekly earnings increased 0.3 percent over the month due to the increase in real average hourly earnings combined with no change in average weekly hours. From January 2015 to January 2016, real average hourly earnings increased 1.3 percent, seasonally adjusted. The increase in real average hourly earnings combined with no change in the average workweek resulted in a 1.3-percent increase in real average weekly earnings over this period.

 

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Real Earnings Technical Note:

The earnings series presented in this release are derived from the Bureau of Labor Statistics’ Current Employment Statistics (CES) survey, a monthly establishment survey of employment, payroll, and hours. The deflators used for constant- dollar earnings series presented in this release come from the Consumer Price Indexes Programs. The Consumer Price Index for All Urban Consumers (CPI- U) is used to deflate the all employees series, while the Consumer Price Index for Urban Wage Earners and Clerical Workers (CPI-W) is used to deflate the production employees series.

Seasonally adjusted data are used for estimates of percent change from the same month a year ago for current and constant average hourly and weekly earnings. Special techniques are applied to the CES hours and earnings data in the seasonal adjustment process to mitigate the effect of certain calendar-related fluctuations. Thus, over-the-year changes of these hours and earnings are best measured using seasonally adjusted series. A discussion of the calendar-related fluctuations in the hours and earnings data and the special techniques to remove them is available in the February 2004 issue of Employment and Earnings or on the Internet under ‘Technical Notes’ (http://www.bls.gov/ces/).

Earnings series from the monthly establishment series are estimated arithmetic averages (means) of the hourly and weekly earnings of all jobs in the private nonfarm sector of the economy, as well as of all production and nonsupervisory jobs in the private nonfarm sector of the economy. Average hourly earnings estimates are derived by dividing the estimated industry payroll by the corresponding paid hours. Average weekly hours estimates are similarly derived by dividing estimated aggregate hours by the corresponding number of jobs. Average weekly earnings estimates are derived by multiplying the average hourly earnings and the average weekly hours estimates. This is equivalent to dividing the estimated payroll by the corresponding number of jobs The weekly and hourly earnings estimates for aggregate industries, such as the major industry sector and the total private sector averages printed in this release, are derived by summing the corresponding payroll, hours, and employment estimates of the component industries. As a result, each industry receives a “weight” in the published averages that corresponds to its current level of activity (employment or total hours). This further implies that fluctuations and varying trends in employment in high-wage versus low- wage industries as well as wage rate changes influence the earnings averages.

There are several characteristics of the series presented in this release that limit their suitability for some types of economic analyses. (1) The denominator for the all employee weekly earnings series is the number of private nonfarm jobs. Similarly, the denominator of the production employee weekly earnings series is the number of private nonfarm production and nonsupervisory employee jobs. This number includes full-time and part-time jobs as well as the jobs held by multiple jobholders in the private nonfarm sector. These factors tend to result in weekly earnings averages significantly lower than the corresponding numbers for full-time jobs. (2) Annual earnings averages can differ significantly from the result obtained by multiplying average weekly earnings times 52 weeks. The difference may be due to factors such as turnovers and layoffs. (3) The series are the average earnings of all employees or all production and nonsupervisory jobs, not the earnings average of “typical” jobs or jobs held by “typical” workers. Specifically, there are no adjustments for occupational, age, or schooling variations or for household type or location. Many studies have established the significance of these factors and that their impact varies over time.

Seasonally adjusted data are preferred by some users for analyzing general earnings trends in the economy since they eliminate the effect of changes that normally occur at the same time and in about the same magnitude each year and, therefore, reveal the underlying trends and cyclical movements. Changes in average earnings may be due to seasonal changes in the proportion of workers in high-wage and low-wage industries or occupations or to seasonal changes in the amount of overtime work, and so on.

 

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