Academic journal article Monthly Labor Review

All-Employee Hours and Earnings for States and Metropolitan Areas

Academic journal article Monthly Labor Review

All-Employee Hours and Earnings for States and Metropolitan Areas

Article excerpt

The Current Employment Statistics (CES) survey, conducted by the U.S. Bureau of Labor Statistics (BLS), is a monthly survey of more than 400,000 business establishments. (1) The CES program provides estimates of employment, hours, and earnings, by industry detail, for the Nation, States, and metropolitan areas. CES data are widely considered one of the most timely and accurate economic indicators published by the Federal Government.

The BLS has published estimates of hours and earnings of production workers since 1909. Because these workers are about 80 percent of all employees (as measured by the CES survey), their hours and earnings data are by no means complete information about the total private economy. Accordingly, the BLS began publishing all-employee hours and earnings data on an experimental basis on March 11, 2008, in order to provide a more complete picture of employee hours and earnings than what is available with the production worker data. The all-employee payroll data provide comprehensive information suitable for analyzing economic trends.

Official publication of State and area CES all-employee payroll data began on March 10, 2010. States are required to publish, at a minimum, all-employee hours and earnings data (1) for all statewide major industry sectors that have a sufficient sample and (2) at the total private-industry level for each metropolitan statistical area. Data on certain industries--for example, trade, transportation, and utilities; professional and business services; and leisure and hospitality--are available for every State. Other highly reported industries include construction (for 49 States), manufacturing (46 States), and education and health services (48 States).

Production worker hours and earnings

Previously, the only series universally produced at the statewide level was production worker hours and earnings for manufacturing. Therefore, there is a basis, albeit limited, for comparison with the new all-employee hours and earnings. It is expected that, in most of the goods-producing industries in which companies depend on the output produced by these workers, the average weekly hours of production workers will be higher than the more comprehensive all-employee measure. Table 1 presents a State-by-State comparison of all-employee and production worker average weekly hours in manufacturing at two different points in time. The new all-employee hours and earnings data series began in January 2007, so that is where an initial comparison can be made.

In January 2007, out of 45 States that reported both all-employee and production worker average weekly hours in manufacturing, 34 showed the latter to be greater than the former. The largest differences occurred in Alaska (5.2 hours), South Dakota (5.1 hours), and Idaho (4.5 hours). Also of note is that 15 out of the 45 States reported production worker hours to be greater than all-employee hours by at least 2 hours.

By October 2009, the gap between production worker and all-employee hours diminished somewhat. Out of 45 States reporting both, production worker hours were greater in 30. The largest differences also diminished, with the top three now being 3.8 hours, in Michigan; 3.4 hours, in Virginia; and 3.3 hours, in South Dakota. In October 2009, only 7 States showed a difference of at least 2 hours between production worker and all-employee hours. The national data, shown in italics, also suggest that the gap between the two kinds of hours lessened between January 2007 and October 2009: the difference at the national level fell from 1.2 hours to 0.9 hour over that period. Average weekly hours declined for both production workers and all employees, with the former showing a stronger drop, an indication that the recession, which began in December 2007, has affected production workers' average weekly hours more than it has all employees'.

A similar comparison can be made with the use of average hourly earnings data. …

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