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Tag Archives: Labor composition

Remembering Dale Jorgenson

The economics profession recently lost one of our leading scholars, Dale W. Jorgenson of Harvard University. His passing leaves a void in the landscape of economic theory, measurement, and data collection. Professor Jorgenson, in so many ways, was a major architect of this landscape, beginning with his early work developing a model of investment. He realized the importance of having theoretically sound measures and accurate data. Throughout his career, Professor Jorgenson’s research, as John Fernald wrote, applied “clear theory, data consistent with that theory, and sound econometrics” to stubborn economic problems and in doing so, built the theoretical, measurement, and data frameworks that underpin economic analysis worldwide.

He was the first to develop a theoretically sound method of measuring capital cost and the rental price of capital, which replaced previous ad hoc empirical work. This early work, which is just a single thread of Professor Jorgenson’s prolific research, is woven into countless aspects of modern-day economics, including the “Solow-Jorgenson-Griliches” growth accounting framework used to measure productivity. Professor Jorgenson made crucial contributions that changed how economists think about investment and how economists understand and measure productivity growth. Innumerable additional threads from Professor Jorgenson’s work permeate modern economics. In his remarkable professional life, Professor Jorgenson’s research furthered economic theory, strengthened economic measurement, and improved and broadened data collection.

Professor Jorgenson’s contributions were particularly important in the areas of investment modeling, growth accounting, national account development, and econometric modeling. His work with Zvi Griliches on the importance of using chain-linked Divisia indexes to measure output and input quantities eventually led to the adoption of these indexes in the U.S. national accounts. In the 1967 classic paper “The Explanation of Productivity Change,” Professors Jorgenson and Griliches developed a model that uses service prices to account for shifts to more productive forms of capital and similarly uses data on labor skills to account for shifts towards more productive forms of labor hours. This model of capital and the work on capturing the heterogeneous nature of labor input are now integral to productivity measurement not only here at BLS but worldwide.

The Organization for Economic Cooperation and Development and the United Nations System of National Accounts have embraced and recommended Professor Jorgenson’s growth accounting system, and statistical agencies throughout the world have adopted it. In the last 40 years, Professor Jorgenson has played a key role in how the Bureau of Economic Analysis produces the National Accounts. Through his 2006 book, “A New Architecture for the U.S. National Accounts,” Professor Jorgenson moved national accounting towards a fully integrated set of accounts, identified gaps and inconsistencies in the accounts, and incorporated nonmarket activities into accounts. Using his ideal Jorgenson System of National Accounts, Professor Jorgenson developed new national accounting features that statistical agencies in many countries have adopted. His work has contributed substantively to the National Income Accounts methods used throughout the world.

Professor Jorgenson also worked to develop an internationally consistent “KLEMS” growth accounting framework by initiating projects to generate industry-level data on outputs, inputs, and productivity in the European Union in 2000, India in 2009, and Asia in 2010. By 2010, the World KLEMS project was underway to further broaden this effort, with a Sixth World KLEMS conference to be held in October 2022. The influence of his research on growth accounting and national accounts extended to the G7 countries and China.

Throughout his career, Professor Jorgenson supported the U.S. statistical community by serving in many capacities: president of the Econometric Society (1987) and the American Economic Association (2000); member of the National Academy of Sciences since 1978, Founding Member of the Board on Science, Technology, and Economic Policy of the National Research Council in 1991 and Chair from 1998 to 2006; member of the Bureau of Economic Analysis Advisory Committee for two decades, serving as Chair from 2004 to 2011; and member of the U.S. Commerce Secretary’s Advisory Committee on Measuring Innovation in the 21st Century Economy from 2006 to 2008.

Professor Jorgenson received numerous awards for his research and service to the statistical system, including the Julius Shiskin Award in 2010, the Adam Smith Award in 2005, and the prestigious John Bates Clark medal in 1971. Professor Jorgenson was never awarded the Nobel Prize in economics, although many people, including myself, view this as an oversight.

As a guiding light on the frontier of economics, particularly in the fields of productivity measurement and national accounting, Professor Jorgenson showed the U.S. and international statistical communities the path forward. His contributions were immense, and many here in the United States and worldwide will grievously feel his loss.

Note: Dr. Lucy Eldridge, Associate Commissioner for the Office of Productivity and Technology, contributed significantly to this post.

Expanding BLS Data on Total Factor Productivity

Our data on multifactor productivity are getting a makeover. You’ll get the same great data but with a new name, “total factor productivity.” Why change the name if it’s the same data? To reach you! More web searches seek total factor productivity than multifactor productivity. That’s probably because most other countries, including our major trading partners, call it total factor productivity. We want to make it easier to find us and stop having to answer how multifactor productivity differs from total factor productivity. They’re the same thing!

Besides the name change, we will expand our annual release of trends in total factor productivity for manufacturing to include not only manufacturing, but all the major industries in the private sector. With this addition, total factor productivity measures for all private major industries of the economy will be available in our news release and the BLS database.

Back to Basics

For those new to productivity data, let’s back up a bit. What is productivity and why should we care about it?

Productivity is a measure of economic performance, often touted as the engine of a nation’s economic growth. Productivity compares the output of goods and services with the inputs used to produce them. The difference in growth rates between these two amounts—the unexplained portion—equals productivity growth. Productivity tells us how good we are at using the inputs to create the output.

Productivity growth is important because, in the long run, it accounts for a third of the growth in a nation’s output. This growth supports increased wages, profits, public sector revenue, and global competitiveness. There are two types of productivity measures produced by BLS, labor productivity and total factor productivity. They are similar, as you can see in the chart below, but they have key differences.

Labor and total factor productivity, annualized percent change, private nonfarm business, 2010–19

Editor’s note: Data for this chart are available in the table below.

Much of the limelight goes to labor productivity, output per hour worked, which measures how many hours it takes to produce the goods and services in our economy. This measure is pretty simple to interpret and apply. If you used the same number of hours but produced more goods and services than last year, the economy became more efficient and labor productivity increased. Labor productivity increased because something besides worker hours (which we know stayed the same) contributed to the increased output. That something is productivity—the growth we didn’t account for in the calculation. With labor productivity, we only account for one input—hours worked. All the other inputs to production, like capital investment and materials, get lumped together into the unknown efficiency gains that can result from changes in technology or how work is organized.

This is where total factor productivity comes in. As the name suggests, total factor productivity measures more than just labor as an input to producing goods and services. It puts more “knowns” into the equation to help us pinpoint a more detailed story of why productivity is changing. For an industry, total factor productivity measures the output produced by a combined set of inputs: capital, labor, energy, materials, and purchased services. Total factor productivity tells us how much more output can be produced without increasing any of these inputs. The more efficiently an industry uses its inputs to create output, the faster total factor productivity will grow.

Total factor productivity gives us great insight into what drives economic growth. Is it the industries’ choice of capital investment? Better or more skilled labor? Or is it a change to the other factors of production, such as energy expenditures, materials consumed, or services purchased, or more efficient use of these inputs? The more detail with which we measure an industry, the more we can learn how these choices contribute to growth in this industry and ultimately our economy.

Let’s recap what we know:

Total factor productivity = output ÷ (combined inputs of capital, labor, energy, materials, and services)

And if we rearrange this equation and transform it to growth over time, we can see that increasing total factor productivity is a way to increase our nation’s output growth.

Output growth = total factor productivity growth + combined inputs growth

More is More

Previously, the annual release on Multifactor Productivity Trends in Manufacturing brought you information on the manufacturing sector and its 19 detailed industries. The manufacturing sector has often been a pioneer of technological development that drives productivity growth and is thus an important sector of the nation’s economy. You can see just how big of a role it has played in productivity growth in The Economics Daily.

And now we are providing a more complete picture. Not only will you get the first comprehensive look into what the COVID-19 pandemic in 2020 meant for labor, capital, and more, but we also will include all major industries and not just manufacturing. The chart below gives a taste of the expanded information that we will now include in the reimagined release with a new name. For example, we can see that in 2019, the information industry had strong output growth (third highest), stemming mostly from combined inputs growth and total factor productivity growth (those things that are harder to measure).

Percent change in total factor productivity, combined inputs, and output, by major private industry, 2019

Editor’s note: Data for this chart are available in the table below.

Connecting Total Factor Productivity to Labor Productivity

We can use total factor productivity and combined inputs for more than just an explanation of output growth. These measures give us is a way to break down the growth of labor productivity. We are the Bureau of Labor Statistics after all, so using our data to understand the growth in efficiency of the nation’s workforce is important.

We can express labor productivity growth as the sum of the growth of six components:

  • Total factor productivity
  • Contribution of capital intensity
  • Contribution of labor composition (shifts in the age, education, and gender composition of the workforce)
  • Contribution of energy
  • Contribution of materials
  • Contribution of purchased services

The contribution of each input is the ratio of the services provided by that input to hours worked. When we look at the contribution of each input, we can measure the effect of increasing the use of that input on an industry’s labor productivity.

The chart below shows sources of labor productivity in 2019 for each industry. The information industry had the second largest increase in labor productivity, rising 5.9 percent. That increase was driven by an increase in capital of 2.8 percent and total factor productivity growth of 1.5 percent. Knowing what drives productivity helps businesses make better decisions and pass those efficiencies on to workers and customers.

Sources of labor productivity change (in percentage points) by major private industry, 2019

Editor’s note: Data for this chart are available in the table below.

We will release new annual data for Total Factor Productivity in 2020 on November 18, 2021, at 10:00 a.m. Eastern Time. More detailed industry data are also available. For more information on productivity check, out our Productivity page. Want to help us improve our productivity data and publications? Please fill out our 10-minute survey by November 16, 2021.

Labor and total factor productivity, annualized percent change, private nonfarm business, 2010–19
YearLabor ProductivityTotal Factor Productivity

2010

3.4%2.7%

2011

-0.1-0.1

2012

0.80.7

2013

0.50.1

2014

0.80.6

2015

1.61.1

2016

0.4-0.4

2017

1.20.5

2018

1.50.9

2019

1.80.7
Percent change in total factor productivity, combined inputs, and output, by major private industry, 2019
IndustryOutputCombined inputsTotal Factor Productivity

Mining

6.7%2.0%4.6%

Management of companies

6.32.33.9

Information

5.74.21.5

Professional and technical services

3.72.21.5

Administrative and waste services

3.52.41.1

Real estate and rental and leasing

2.82.40.4

Accommodation and food services

2.82.10.7

Retail trade

2.30.51.7

Health care and social assistance

2.31.70.7

Transportation and warehousing

2.12.10.0

Arts, entertainment, and recreation

2.10.51.5

Finance and insurance

1.93.0-1.1

Agriculture, forestry, fishing, and hunting

0.50.8-0.3

Educational services

0.10.6-0.5

Construction

-0.70.7-1.4

Other services, except government

-0.8-2.21.3

Utilities

-1.1-4.63.6

Nondurable manufacturing

-1.60.3-1.9

Manufacturing

-1.70.3-2.0

Durable manufacturing

-1.80.1-1.9

Wholesale trade

-2.10.0-2.1
Sources of labor productivity change (in percentage points) by major private industry, 2019
IndustryServices intensityMaterials intensityEnergy intensityLabor compositionCapital intensityTotal Factor Productivity

Management of companies

1.9-0.10.00.50.03.9

Information

1.40.10.00.12.81.5

Mining

1.1-0.7-0.10.5-0.64.6

Arts, entertainment, and recreation

1.70.00.0-0.21.11.5

Administrative and waste services

1.80.30.00.30.31.1

Retail trade

1.70.0-0.10.00.51.7

Accommodation and food services

0.8-0.1-0.20.20.00.7

Finance and insurance

1.60.00.00.10.9-1.1

Professional and technical services

-0.1-0.20.0-0.10.31.5

Health care and social assistance

0.1-0.3-0.10.20.10.7

Real estate and rental and leasing

0.5-0.1-0.20.00.00.4

Utilities

-1.40.2-3.30.01.63.6

Other services, except government

-0.8-0.3-0.10.00.11.3

Agriculture, forestry, fishing, and hunting

0.00.4-0.30.1-0.3-0.3

Nondurable manufacturing

0.3-0.1-0.10.10.6-1.9

Manufacturing

0.00.1-0.20.00.5-2.0

Durable manufacturing

-0.20.1-0.10.00.4-1.9

Transportation and warehousing

-1.20.3-1.0-0.3-0.10.0

Wholesale trade

-1.00.0-0.10.10.7-2.1

Construction

-0.3-1.3-0.20.00.1-1.4

Educational services

-2.20.2-0.4-0.1-0.1-2.2