On June 4, 2019, the Bureau of Labor Statistics (BLS) published experimental state-level labor productivity and cost measures for the private nonfarm sector starting in 2007, including output per hour, output, hours, unit labor costs, hourly compensation, and real hourly compensation. By analyzing state-level labor productivity measures, data users can learn more about regional business cycles, the persistence of regional income inequality, and which states are driving national productivity trends.
BLS published an article, "BLS Publishes Experimental State-level Labor Productivity Measures", that describes the data and methodology used to estimate these new labor productivity data. In addition, the article examines the compensation-productivity gap, the relationship between productivity growth and the share of output in the information and communications technology producing sector, and whether state-level labor productivity is converging following the Great Recession.
On June 11, 2020, BLS published both 2018 and 2019 state-level labor productivity and cost measures. While the 2018 data strictly follow the methodology outlined in the aforementioned article, the 2019 data follow the methodology with additional estimations of components that are not yet available for output, labor, and compensation measures. As a result of this, 2019 data is subject to revision next year, during which BLS plans to roll out revised numbers for 2019 and preliminary numbers for 2020.
Annual growth rates for select measures
Download: Annual Growth Rates (XLSX)
Long-term growth rates for select measures
Download: Long-Term Growth Rates (XLSX)
Frequently asked questions
1. How is output measured for states?
BLS state-level measures of output for the private nonfarm sector are created using GDP by state and industry data published by the Bureau of Economic Analysis (BEA). BEA does not produce a private nonfarm sector measure of real output by state. To create the necessary output series, BLS subtracts several industry components — the farm sector, private households, and owner-occupied housing — from GDP by state using a Fisher ideal index formula. See output subsection of MLR article for more information on BEA's methods for nominal and real measures of GDP by state and industry.
2. How is hours measured for states?
Hours are the number of hours worked by all employed persons, including wage and salary workers, self-employed persons, and unpaid family workers. Hours for wage and salary workers are primarily from BLS Current Employment Statistics (CES) and hours for self-employed and unpaid family workers are from the BLS Current Population Survey (CPS). The hours are adjusted from an hours paid basis to an hours worked basis using data from the BLS National Compensation Survey (NCS). See hours subsection of MLR article for more information.
3. What are the differences between the way BLS constructs state-level and national labor productivity measures?
First, the state-level measures cover the private nonfarm sector which adjusts the nonfarm business sector (76% of GDP in 2018) used in national productivity measurement by adding nonprofit institutions serving households and removing government enterprises. Second, the methods used for calculating the average weekly hours worked for wage and salary workers are different. At the state-level, BLS uses the average weekly hours paid for all wage and salary workers data published by the BLS Current Employment Statistics (CES) directly. At the national-level, BLS estimates the average weekly hours paid for wage and salary production and nonproduction workers separately. At both the state and national level, BLS adjusts hours from a paid basis to a worked basis using data from the BLS National Compensation Survey (NCS). See differences between state and national productivity measures subsection of MLR article for more information.
4. What are 'experimental' measures?
The BLS state-level productivity measures are classified as an experimental series, meaning the measures will continue be evaluated and adjusted as improvements are identified. For example, BLS is currently exploring alternative methods that will better align state and national productivity data. BLS is also soliciting feedback on these new measures from all data users. Comments can be submitted through the Productivity Contact Webpage or e-mailed directly to email@example.com.
Last Modified Date: June 11, 2020