PRODUCTIVITY MEASUREMENT Managerial Economics

Productivity analysis and measurement is important at the company, industry, and economy-wide levels. For the overall economy, growing economic productivity makes possible improvements in the economic welfare of the general population. From the company’s perspective, productivity betterment holds the key to growing profits and employee compensation.

How Is Productivity Measured?

Studies of output per hour in individual industries and the overall economy have been a responsibility of the Bureau of Labor Statistics (BLS) since the 1800s. A study of 60 manufacturing industries, prompted by congressional concern that human labor was being displaced by machinery, was released as Hand and Machine Labor in 1898. This report provided striking evidence of the savings in labor resulting from mechanization in the last half of the nineteenth century. The effects of advances in productivity on employment remained an important focus of the BLS throughout the 1920s and 1930s. During this period, the Bureau began preparation and publication of industry productivity indexes based upon production data from the periodic Census of Manufactures and employment statistics collected by BLS. In 1940, Congress authorized the BLS to undertake continuing studies of productivity and technological change. The onset of World War II caused a change in emphasis from apprehension of unemployment to concern with making the most efficient use of scarce labor resources. In recent years, public interest in productivity measurement and enhancement has grown as expanding worker productivity has been recognized as an important indicator of economic progress.

One of the most prominent uses of economic survey information is to track the pace of economic betterment, or productivity growth, in the overall economy. Productivity growth is the rate of increase in output per unit of input. Labor productivity refers to the relationship between output and the worker time used to generate that output. It is the ratio of output per worker hour. In multifactor productivity measures, output is related to combined inputs of labor, capital, and intermediate purchases. Worker input is measured by the number of hours of labor expended in the production of output. Capital includes expenditures for equipment, structures, land, and inventories. Intermediate purchases are composed of expenditures for materials, fuels, electricity, and purchased services.

Advances in productivity reflect the ability to produce more output per unit of input. Such advances are a significant source of growing national income and rising economic betterment. Over time, the U.S. economy has been able to produce more goods and services, not just by employing more labor and other inputs, but by making production more efficient. Production is becoming more efficient in a number of ways. Increased training and education make workers increasingly productive. Invention and innovation lead to improved capital equipment; advances in management techniques lead to better organization design and improvements in worker incentives.

Improvements in worker productivity are measured by taking an index series for output and dividing it by an index series for employee hours. Both “factory floor” or production workers and office workers are included in employee hours. Although separate data are collected for production workers and nonproduction workers, only the sum of the two is used in productivity measurement because it is impossible to determine what share of output is attributable to production versus nonproduction workers.

Increases in multifactor productivity are evaluated by dividing an index series for output by an index series for the combined inputs of labor, capital, and intermediate purchases. Each index series is simply a way of expressing, in percentage terms, the change in some variable from a given point in time to another point in time. For example, let’s say that output increased by 10 percent from an initial year (2001) to a subsequent year (2002). The index for our arbitrarily chosen base year of 2001 would be 100; the index for 2002 would be 110. Conversely, if output had declined in 2002 by 10 percent, the 2002 index value would be 90. If an industry produced only one product, calculating an output index series would be simple. However, that is seldom true. Most often, it is necessary to account for productivity changes among industries that produce many different products, and products that change dramatically over time. Figure illustrates how productivity, measured as output per hour in the private nonfarm sector, accelerated during the late 1990s. Productivity growth more than doubled from an annual rate of 1.4 percent per year before 1995 to an annual rate of 3 percent from 1995 through 2000.

Without a doubt, some of this increase can be described as the typical change in productivity growth that occurs over the business cycle. During economic booms, like that enjoyed during the late 1990s, productivity growth tends to rise as factories move towards full utilization. During recessions, productivity growth lags with worker layoffs and plant closings. However, even if as much as 0.5 percent of the late 1990s boost in productivity growth can be attributed to business cycle effects, a structural acceleration in productivity growth of at least 1 percent has taken place. Although economists are yet uncertain about the relative magnitude of cyclical versus structural influences, all agree that productivity growth has been helped by an increase in the amount of capital per worker hour (capital deepening) and by improvements in the measurable skills of the work force (labor quality).

A significant share of the recent boost in productivity growth is attributable to broader economic forces. Specifically, more effective use of worker skills has become possible through recent improvements in communications technology. Increasingly, companies have been eager to buy powerful computers and computer software at relatively low prices. Rapid advances in computer hardware and software technology, combined with the widespread adoption of the Internet, have led to an unprecedented boom in communications technology. Benefits from the recent boom in communications technology are evident in every home and workplace, and are broadly reflected in the late 1990s burst in productivity growth.

Trends in Industry Productivity

Industry productivity measures describe the relationship between output and the labor time involved in its production. They show the changes from period to period in the amount of goods and services produced per hour. Although these measures relate output to hours of employees or all persons engaged in an industry, they do not measure the specific contribution of labor, capital, or any other factor of production. Rather, they reflect the joint effects of many influences, including changes in technology; capital investment; level of output; utilization of capacity, energy, and materials; the organization of production; managerial skill; and the characteristics and effort of the workforce.

Productivity Growth Jumped in the Late 1990s

Productivity Growth Jumped in the Late 1990s

To calculate productivity measures for industries with diverse and changing output, different products are aggregated into one output measure by weighting (multiplying) the relative change in output of each product by its share in the total value of output. In this way, higher value products that require more resources to produce are given higher weight. For tangible products, such as tons of steel, developing an output index series and productivity measures can be fairly straightforward. In other industries, particularly in the services sector, developing output indexes and productivity measures is more challenging. In many instances, data for the quantities of output produced or the number of times a service has been performed are not available. However, changes in revenue are typically available, and changes in revenue reflect changes in both the quantity of output and its price. Price changes can be accounted for by dividing an index of revenue by a price index. This leaves an index of quantity that can be used to measure productivity.

Industry studies cover a variety of manufacturing and nonmanufacturing industries at the sector, industry group, and industry-level classifications. Measures for over 175 industries are published on an annual basis, beginning as early as 1947. Coverage includes industries in the manufacturing, mining, trade, transportation, communication, public utilities, finance, and business and personal services sectors. In addition to measures of industry worker productivity, BLS publishes multifactor productivity statistics for certain industries. First released in 1987, industry multifactor productivity measures relate output to the combined inputs of labor, capital, and intermediate purchases. Unlike worker productivity measures, multifactor productivity measures are free from the effects of changes in the ratio of capital to labor and alterations in the ratio of intermediate purchases to labor. Because of the enormous data requirements for the measurement of capital and intermediate purchases, only a limited number of industry multifactor productivity measures has been published. As shown in Figure, almost all manufacturing industries posted productivity gains from 1990 to 1999. Output per hour increased in 111 of the 119 industries. Productivity advanced an amazing 5 percent per year in 12 industries. Another 49 industries experienced exceptional annual productivity growth in the 2.5–4.9 percent range. Computer and office equipment posted the largest average annual gain, 33.3 percent. The five largest manufacturing industries all registered growth in output per hour from 1990 to 1999. Worker productivity rose a stunning 26 percent in electronic components and accessories; 3.3 percent in miscellaneous plastics products; 3.2 percent in motor vehicles and equipment; 1.3 percent in commercial printing; and 0.6 percent in meat products.

From 1990 to 1999, unit labor costs fell in 34 of the 119 industries in the manufacturing sector. Of the 34 industries, only pulp mills had decreasing worker productivity (–3 percent). The largest declines in unit labor costs were computer and office equipment (–22.3 percent) and electronic components and accessories (–17.6 percent). In the early years of the period, 1990–95, output per hour increased in 106 of the 119 industries. In 20 industries, productivity advanced 5 percent per year or more. An additional 36 industries experienced annual productivity growth in the 2.5–4.9 percent range.

Comparing the 1990–95 period with the 1995–99 period, productivity growth rates increased in 72 of 119 manufacturing industries. In 14 industries, annual output per hour grew at least 5 percentage points faster in 1995–99 than in 1990-95. Another 24 industries posted annual productivity growth rates 2.0–4.9 percentage points above their 1990–95 rates. All 13 of the

Manufacturing Productivity Growth Has Been Impressive

Manufacturing Productivity Growth Has Been Impressive

Industries that experienced productivity declines in the earlier period registered productivity improvements in the later period. Seven of these 13 industries experienced positive productivity growth in the 1995–99 period.

Uses and Limitations of Productivity Data

Measures of output per hour are useful for analyzing trends in labor costs across industries, comparing productivity progress among countries, examining the effects of technological improvements, and analyzing related economic and industrial activities. Such analyses usually require that indexes of output per hour be used in conjunction with other data. Related data on production and employment are useful in studying technological effects. To study trends in labor costs, data on earnings and other labor expenditures must be compiled.

It is important to recognize that productivity measures of output per hour are subject to certain qualifications. Among these is the fact that existing techniques may not fully take into account changes in the quality of goods and services produced. Although efforts have been made to maintain consistency of coverage between the output and labor input estimates, some statistical differences remain that can confound intertemporal comparisons. Estimates of influences tied to nonproduction worker hours, unpaid family workers, the self-employed, and paid managers are also subject to a wide margin of error. Finally, year-to-year changes in output per hour are sometimes irregular and, therefore, are not necessarily indicative of basic changes in long-term trends. Because of these statistical limitations, productivity measures cannot be considered precise. Instead, they should be interpreted as useful indicators subject to measurement error.

Unfortunately, industry productivity measures are not available at the county, state, or regional level. They are nationwide averages that can sometimes vary from one locale to another.

BLS worker productivity and multifactor productivity indexes are published annually in the bulletin, Productivity Measures for Selected Industries. Indexes of output per hour also are published in the Statistical Abstract of the United States and are available in the Bureau’s LABSTAT database, on BLS data diskettes, or on the Internet at the BLS Web site. A limited amount of the most current data is provided in annual news releases. Technical notes describing the methodology used to develop the indexes are available on request.


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