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The Pay Premium for Manufacturing Workers as Measured by Federal Statistics

Historically, manufacturing jobs have offered relatively high pay. However, there is not a consensus on the size of the pay premium for manufacturing jobs relative to the economy as a whole or even whether a premium continues to exist. This report turns to evidence to answer those questions, using ten federal datasets, each of which allows us to calculate and compare the average pay of manufacturing workers and the average pay of workers overall. The following datasets are included:

  • American Community Survey
  • County Business Patterns
  • Current Employment Statistics
  • Current Population Survey
  • Economic Census
  • Employer Costs for Employee Compensation
  • National Income and Product Accounts
  • Occupational Employment Statistics
  • Quarterly Census of Employment and Wages
  • Quarterly Workforce Indicators

In addition, these datasets allow us to examine comparisons of average pay that control for various factors that could affect the estimated pay premium, such as whether the data measures pay on an hourly basis or for some other period, and which workers are included in the pay premium estimate. Generally, we find evidence of a pay premium regardless of which dataset we examine. However, the size of the premium is increased or decreased by various factors.

Key findings from the analysis include:

  • Based on hourly wages and salaries, manufacturing workers earn more on average than the overall average worker: using data for 2013, estimates of
  • the hourly pay premium vary from 2 to 9 percent, depending on the dataset used. 
  • When hours worked in a week or over the course of a year are taken into consideration, the estimated premium increases. Estimated premiums using weekly or annual pay data are as high as 32 percent. This larger premium is because manufacturing employees work longer hours per week and more hours per year on average.
  • Because the manufacturing sector has a high proportion of full-time workers relative to other private sector industries, the pay premium is smaller when the estimates are restricted to full-time workers, in one case declining from 32 percent for all workers to 12 percent for full-time employees.
  • Data that distinguishes new hires from all workers finds that both groups enjoy a pay premium in the manufacturing sector, with new hires earning a larger premium than other workers.
  • The size of the premium also varies greatly depending on the occupation. For some occupations, manufacturing workers earn less than workers overall. At the other extreme, manufacturing workers in sales occupations earn 64 percent more than their counterparts in non-manufacturing sales occupations throughout the economy.
  • Estimates of a manufacturing pay premium should use the dataset and comparison groups that best suits the particular question at hand. Datasets providing estimates of hourly pay might be more appropriate for estimating a premium based solely on wages, but datasets providing estimates of weekly, monthly or annual pay might provide greater insights about worker incomes.
  • Additional research is needed to better understand the underlying factors that drive the manufacturing premium.  The heterogeneity of the manufacturing sector and its workforce suggests that both worker characteristics, such as occupational and educational attainment, and employer characteristics, such as firm size and age and specific industry, could play a role in the premium.  Regression analyses that control for such factors can help identify their importance in the overall premium.
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