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Kenneth W. Robertson

robertson.ken@bls.gov

Kenneth W. Robertson is the Assistant 

Commissioner for the Office of Industry 

Employment Statistics, U.S. Bureau of Labor 

Statistics.

Benchmarking the Current Employment Statistics 

survey: the past, present, and future

In the sample survey world, benchmarking is aligning a 

survey-based estimate with a population value. The Current 

Employment Statistics (CES) survey has benchmarked its 

employment estimates since 1935. This article introduces a 

set of four additional articles on this topic. These articles 

discuss the current benchmark practices, provide a general 

overview of research on benchmarking the CES data, and 

investigate a methodology that may ultimately improve 

those procedures.

Background

CES data, which include estimates of employment, hours, 

and earnings by industry for the nation, states, and 

metropolitan areas, are designated by the Office of 

Management and Budget as a principal federal economic 

indicator. These data are published at the national level 

about 3 weeks after the reference period, which is the pay 

period that includes the 12th, and at the state and area 

level about 5 weeks after the reference period. Because of 

the timeliness and accuracy of the data, they are used as a 

major factor in assessing the health of the national, state, 

and area economies.

The CES survey has an unusual feature that most sample surveys do not have: it retrospectively adjusts its 

primary estimate of employment to a population value. For CES, this population value is a combination of data 

primarily from the U.S. Bureau of Labor Statistics (BLS) Quarterly Census of Employment and Wages (QCEW), 

with additional data to account for employment not covered by QCEW. In adjusting this estimate to a population 

value, CES has what is essentially a measure of total survey error. In reality, this measure is an alignment of two 

values, each with its own sources of error. Nevertheless, this measure is a valuable tool in assessing the quality of 

the data from the CES survey.

CES data give a very timely measure of the health of the economy. Because of this, there is substantial interest in 

anything that might assess the quality of that data and in anything that might improve forecasts of the economy 

built with CES data as an input. Many data users compare CES estimates with data from the lagged QCEW when 

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they become available each quarter. By comparing these data, the data user is using the most recently available 

QCEW data to be informed of the potential size and direction of error in the more timely CES estimates. Data 

users are finding this quarterly evaluation to be highly valuable; therefore, BLS should consider benchmarking the 

CES data more frequently.

The goal of this set of articles is to describe for the reader the current methods used for CES benchmarking, to 

provide a bit of history about the CES survey and about its benchmarking procedures and related research, and to 

examine what a future procedure may look like.

Current practices

The CES survey currently aligns its data to population values using one benchmark procedure for national data 

and using another procedure for its state and area data. Briefly, the national procedure aligns its prior March 

estimates with a population estimate for that month, whereas the state and area data are benchmarked by 

replacing all months prior to March with population estimates. Two articles describe in more detail the current 

benchmark procedures, one for national estimates and one for state and area estimates.

Overview of research

A third article briefly discusses the history of CES benchmarking and summarizes current procedures. The article 

then describes one of the methods that some data users outside of BLS are using to develop early benchmarked 

estimates, by taking advantage of the quarterly publication of QCEW data. Next, the article describes why CES 

has not yet started benchmarking more than once a year; the reasons are focused on different seasonal patterns 

in the survey and population estimates and on resource constraints. Finally, the article provides an overview of 

recent research to find improvements to the current procedures.

A promising methodology

The fourth article examines the most promising benchmarking method researched to date. This method explicitly 

considers the different seasonal patterns in the survey and population data. Methods that do not explicitly account 

for the different seasonal patterns have proven to be unsatisfactory.

SUGGESTED CITATION

Kenneth W. Robertson, "Benchmarking the Current Employment Statistics survey: the past, present, and future," 

Monthly Labor Review, U.S. Bureau of Labor Statistics, October 2017, https://doi.org/10.21916/mlr.2017.24

RELATED CONTENT

Related Articles

Benchmarking the Current Employment Statistics national estimates, Monthly Labor Review, October 2017.

Benchmarking the Current Employment Statistics state and area estimates, Monthly Labor Review, November 2017.

Benchmarking the Current Employment Statistics survey: perspectives on current research, Monthly Labor Review, November 2017.

A quarterly benchmarking procedure for the Current Employment Statistics program, Monthly Labor Review, November 2017.
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Related Subjects

Survey methods Benchmarking Sampling Seasonal adjustment Survey procedures