Overview

Mission

Two programs develop multifactor productivity data for elements of the U.S. economy.  The Major Sector Multifactor Productivity program develops indexes of multifactor productivity for the private business and private nonfarm business sectors of the economy and for the aggregate manufacturing sector, as well as for 18 3-digit North American Industry Classification System (NAICS) manufacturing industries and the utility and gas industry (SIC 49).  The Industry Multifactor Productivity program develops indexes of multifactor productivity for 86 4-digit NAICS manufacturing industries, air transportation, and railroad transportation.  Multifactor productivity measures for the manufacturing sectors of selected countries are also available.

Multifactor productivity measures relate output to two or more inputs, depending on the definition of the particular multifactor productivity measure.  This contrasts to labor productivity measures, which relate output to a single input, labor.

Comparisons among multifactor productivity measures must be made with an understanding of the underlying definitions used in constructing each measure.  The multifactor productivity measures produced by the Bureau use two distinct concepts of real output which are characterized as gross product originating and sectoral output.  For private business, private nonfarm business, and international multifactor productivity measures, a gross product originating measure is used.  For manufacturing and industry multifactor measures, a sectoral output measure is used.

Background

Description of Measures

The BLS multifactor productivity measures were first introduced in Trends in Multifactor Productivity, 1948-81, Bulletin 2178, September, 1983, and have been updated annually.

Multifactor productivity measures reflect output per unit of some combined set of inputs.  A change in multifactor productivity reflects the change in output that cannot be accounted for by the change in combined inputs.  As a result, multifactor productivity measures reflect the joint effects of many factors including new technologies, economies of scale, managerial skill, and changes in the organization of production.

Since 1983, the multifactor productivity measurement program has expanded from producing measures for the major sectors of the U.S. economy only (private business, private nonfarm business, and manufacturing sectors) to include multifactor measures for 18 3-digit NAICS manufacturing industries,  86 4-digit NAICS manufacturing industries, air transportation, and railroad transportation.  In addition there are multifactor measures for the manufacturing sectors of selected foreign countries.

In 2006, BLS revised the multifactor productivity measures for the manufacturing sector as a whole and also began reporting multifactor productivity for manufacturing industries at the 3-digit NAICS level.  These changes are described in the December, 2006 press release, "Multifactor Productivity Trends in Manufacturing, 2002, 2003, and 2004."

The multifactor productivity indexes for major sectors measure value-added output per combined unit of labor and capital input in private business and private nonfarm business. BLS measures multifactor productivity in total manufacturing and the 18 3-digit NAICS manufacturing industries as output per unit of combined capital (K), labor (L), energy (E), materials (M), and purchased service inputs (S).  These are often referred to as the KLEMS inputs.  The most recent data for the U.S. private business, private nonfarm business, and manufacturing sectors, including 18 3-digit NAICS manufacturing industries, are available in the Multifactor Productivity Trends and Multifactor Productivity Trends in Manufacturing news releases.

The detailed industry multifactor productivity measures are constructed in a manner similar to the manufacturing sector series, by calculating the ratio of an output index to an input index comprised of a weighted average of employee hours, capital services, and intermediate purchases (including materials and supplies, energy, and purchased services).  Inputs are weighted together using cost weights representing each input's share of total output to develop the combined inputs index.  Multifactor productivity measures can be thought of as labor productivity measures adjusted to remove the effects of changes in capital per hour and intermediate purchases per hour. MFP data are available as historical time series for 86 4-digit NAICS manufacturing industries, the air transportation industry, and the railroad transportation industry.  The most recent data for the 86 4-digit manufacturing industries are available in the Multifactor Productivity Trends for Detailed Manufacturing Industries news release.

Comparative trend measures of multifactor productivity are also available for the manufacturing sectors of the United States, France, and Germany. These measures relate value-added output to combined labor and capital inputs.

In addition to the multifactor productivity measures, BLS produces measures of labor productivity or output per hour.  A change in labor productivity reflects the change in output that cannot be accounted for by the change in hours worked of all persons.  Labor productivity or output per hour differs from multifactor productivity in its treatment of capital and labor inputs.  Labor productivity measures do not explicitly account for the effects of capital or shifts in the composition of labor.  Labor productivity, then, reflects all of the effects that influence multifactor productivity and the effects of changes in the capital available per worker and shifts in the education attainment and work experience of the work force.

Coverage

Annual multifactor productivity indexes are available for the:

  • Private business and private nonfarm business sectors, from 1987.
  • Aggregate manufacturing and 18 3-digit NAICS manufacturing industries, from 1987.
  • 4-digit NAICS manufacturing industries, air transportation, and railroad transportation, from 1987.
  • France and Germany in total manufacturing, from 1958.

Uses

  • Economic indicator of technical progress and unit factor costs.
  • Basis for research on the sources of productivity advance and the identification of policy options which can affect the pace of productivity change.
  • Aid in understanding trends in output per hour of all persons.
  • Provides a more comprehensive productivity measure, supplementing existing economic indicators, that incorporates capital in addition to labor inputs.
  • Measures of multifactor productivity are useful for analyzing trends in total costs and overall efficiency, and for studying the effects on labor productivity of changes in capital relative to labor and intermediate purchases relative to labor. Multifactor measures are also useful for studying the utilization of the nonlabor inputs - capital and intermediate purchases - over time.

Glossary of Terms

Value-added output is defined as gross output (sales or receipts and other income, plus inventory change) minus intermediate inputs (goods and service inputs purchased from other domestic industries and foreign sources). This is also termed gross product originating, and represents the value that is added by the application of capital and labor to intermediate inputs in converting those inputs to finished products. Further information on this concept of output is available in Measurement of Productivity Growth in U.S. Manufacturing, by William Gullickson, Monthly Labor Review, July 1995, pp. 13-28.PDF

Sectoral output is defined as gross output excluding intra-industry transactions. This measure defines output as deliveries to consumers outside the sector, in an effort to avoid the problem of double-counting that occurs when one establishment provides materials used by other establishments in the same industry. Further information on this concept of output is available in Measurement of Productivity Growth in U.S. Manufacturing, by William Gullickson, Monthly Labor Review, July 1995, pp. 13-28.PDF

The Tornqvist index is a discrete approximation to a continuous Divisia index. A Divisia index is a weighted sum of the growth rates of the various components, where the weights are the component's shares in total value. When a Tornqvist index is used as an approximation to the continuous Divisia index, the growth rates are defined as the difference in natural logarithms of successive observations of the components and the weights are equal to the mean of the factor shares of the components in the corresponding pair of years. The Tornqvist index represents an improvement over constant base-year weighted indexes, because as relative prices of inputs change, the Tornqvist index allows both quantities purchased of the inputs to vary and the weights used in summing the inputs to vary, reflecting the relative price changes. For the labor input measure, the Tornqvist index effectively weights the growth rate of the hours of each group of workers by their share of labor compensation.

Gross product originating in private business equals gross domestic product in the economy less government, private households, and nonprofit institutions. Gross product originating excludes intermediate transactions between businesses.

Real gross domestic product is the output of goods and services produced by labor and property located in the United States. These data are produced by the Bureau of Economic Analysis.  

 

Data

Data Available

  • Annual indexes of multifactor productivity and output per unit of capital services for the private business, private nonfarm business, and manufacturing sectors, published in the Multifactor Productivity Trends News Release.
  • Annual measures of capital services, composition adjusted labor services, and combined labor and capital inputs for the private business and private nonfarm business sectors, available as historical time series on this web site.
  • Annual multifactor productivity measures for 18 3-digit NAICS manufacturing industries which include labor, capital, energy, materials, and purchased business services inputs, available as historical time series on this web site.
  • Annual indexes of industry multifactor productivity which include labor, capital, and intermediate purchases inputs. The most recent data for the 86 4-digit manufacturing industries are published in the Multifactor Productivity Trends for Detailed Manufacturing Industries News Release. These data, as well as data for the air transportation and railroad transportation industries, are available as historical time series on this website.
  • Annual indexes of multifactor productivity for the manufacturing sectors of France and Germany. These data are available as historical time series on this web-site and as data tables on the Foreign Labor Statistics web-page.

Data Sources

Output

For the major sectors (private business and private nonfarm business), manufacturing, and 18 3-digit NAICS manufacturing industries:

Output data are based on series prepared as part of the National Income and Product Accounts by the Bureau of Economic Analysis, U.S. Department of Commerce.

The multifactor productivity measures use two distinct concepts of real output: gross product originating and sectoral output.

For private business and private nonfarm business, output is defined as gross product originating.  Gross product originating in private business equals gross domestic product in the economy less government, private households, and non-profit institutions.  Gross product originating excludes intermediate transactions between businesses.

In manufacturing, a sectoral output measure, defined as shipments from producers to all purchasers including other producers (except producers within the same industry) plus inventory change, is used.  This reflects the increase in output due to the application of capital and labor and intermediate inputs.  The primary distinction between the sectoral output measure used by BLS and a more general "gross output" measure is that the BLS sectoral output measure excludes shipments within the same industry.  So, BLS measures total manufacturing output as the deflated value of shipments outside of the manufacturing industry.

For the private business and private nonfarm business sectors as a whole, intermediate inputs are an extremely small part of the input structure.  As such, they can be considered insignificant to the analysis of productivity growth.  This is not true for manufacturing.  Examples of the importance of intermediate inputs in manufacturing include the rapid increase in energy prices in the 1970s and the increased use of business services, such as equipment leasing and computer services, all of which have affected productivity measurement.

For the 4-digit NAICS manufacturing industries, air transportation, and railroad transportation: Industry output is measured as sectoral output, the total value, in real terms, of goods and services produced for sale outside the industry. For most industries, real output is measured by deflating nominal value of production, but for a few industries it is measured by physical quantities. Industry value of production is derived by adjusting industry shipments for changes in inventories and subtracting intra-industry transfers and resales. Wherever possible, the indexes of industry output are calculated with a Tornqvist formula. This formula aggregates the growth rates of the various industry outputs between two periods, using their relative shares in industry value of production, averaged over the two periods, as weights.

For France and Germany: The Foreign Labor Statistics web-page provides information on the output data used in constructing comparative multifactor productivity measures for France, Germany and the United States.

Labor

For the major sectors (private business and private nonfarm business), manufacturing, and 18 3-digit NAICS manufacturing industries:

Hours and employment data are primarily drawn from the BLS Current Employment Statistics (CES) program, which provides monthly survey data on total employment and average weekly hours of production and nonsupervisory workers in nonagricultural establishments. Jobs rather than persons are counted. Weekly paid hours are adjusted to hours at work using data from the National Compensation Survey (NCS). The BLS Hours at Work Survey (HWS) PDF (12K), conducted for this purpose, was used for years prior to 2001. How to view a PDF file. The Office of Productivity and Technology estimates average weekly hours at work for nonproduction and supervisory workers using information from the Current Population Survey (CPS), the CES, and the NCS.

Data from the BLS Current Population Survey are used for farm labor. In the nonfarm sector, the National Income and Product Accounts prepared by the Bureau of Economic Analysis of the Department of Commerce and the CPS are used to measure labor input for government enterprises, proprietors, and unpaid family workers. All series have been adjusted to take into account the activities of dual jobholders.

Labor composition data are largely based on household surveys and the decennial census. For private business and private nonfarm business, the labor input is an aggregate of the hours worked of all persons classified by their education, work experience and gender.  This aggregate labor input measure is constructed by aggregating hours at work data for each of 1,008 types of workers classified by their educational attainment, work experience and gender using an annually chained Tornqvist index.  The effect of Tornqvist aggregation is to produce a measure of labor input which reflects both changes in total hours of work and changes in the composition of workers.  A shift in the work force toward more educated and experienced workers generally results in faster labor input growth.  The difference between the growth rate of labor input and total hours at work is defined to be the growth rate of labor composition and it is, loosely, a measure of the change in the skill level of the work force.  For all industries or sectors other than private business and private nonfarm business, labor input is identical to total hours at work and does not reflect changes in labor composition.

For the 4-digit NAICS manufacturing industries, air transportation, and railroad transportation:

The industry labor input measures represent the hours of all workers in the industry. The primary source of data on employment and hours is the BLS Current Employment Statistics (CES) survey, which provides monthly data on the number of jobs held by wage and salary workers employed directly in nonfarm establishments. The CES survey also provides data on the average weekly hours of production workers in these establishments. Data from the BLS Current Population Survey (CPS) are used to supplement the CES data. The industry productivity program estimates the average weekly hours of nonproduction workers for each industry using data from the CPS together with the CES data. The hours of all workers are treated as homogeneous and are directly aggregated.

For France and Germany: the Foreign Labor Statistics web-page provides information on the labor data used in constructing comparative multifactor productivity measures for France, Germany and the United States.

Capital

For the major sectors (private business and private nonfarm business), manufacturing, and 18 3-digit NAICS manufacturing industries:

Capital data are based on measures of equipment and structures, land, and inventories prepared by the Bureau of Labor Statistics from data of the Bureau of Economic Analysis and U.S. Department of Agriculture.

Capital input is measured by the services which flow from the stock of capital.  This differs from the stock of capital sometimes used in productivity measurement because not all forms of capital provide services at the same rate.  Short lived assets such as a car or computer must provide all of their services in just the few years before they completely depreciate.  Office buildings provide their services over decades.  So in a year, a dollar's worth of a car provides relatively more services than a dollar's worth of a building.  Because of differences in capital services between assets, capital input can increase not only because investment increases the capital stocks, but also if investment shifts toward assets (such as equipment) which provide relatively more services per dollar of capital stock.

For the 4-digit NAICS manufacturing industries, air transportation, and railroad transportation:

The measure of capital input is based on the flow of services derived from the stock of physical assets. Physical capital is composed of 26 categories of equipment, 2 categories of structures, 3 categories of inventories, and land. Capital services are estimated by calculating capital stocks; changes in the stocks are assumed to be proportional to changes in capital services for each asset. Capital stocks are calculated using the perpetual inventory method, which takes into account the continual additions to and subtractions from the stock of capital as new investment and retirement of old capital occur.

Price changes are removed from the annual investment data before calculating stocks. Price deflators for each asset category are constructed by combining detailed price indexes (mostly PPIs) with weights from the BEA capital flow tables that reflect the individual asset commodities used by each industry.

The index of aggregate capital input for each industry is an annually chained Tornqvist quantity index of the growth rates of the stocks of each type of asset. The growth rates are aggregated using weights that are the average of each asset type's cost share in successive years. The asset costs are estimated by multiplying the asset stocks by implicit rental prices.

For France and Germany: the Foreign Labor Statistics web-page provides information on the capital data used in constructing comparative multifactor productivity measures for France, Germany and the United States.

Intermediate Purchases

For the 18 3-digit NAICS manufacturing industries:

Intermediate inputs (energy, materials, and purchased business services) are obtained from BEA based on BEA annual input-output tables. Tornqvist indexes of each of these three input classes are derived at the 3-digit NAICS level and then aggregated to total manufacturing.

For the 4-digit NAICS manufacturing industries, air transportation, and railroad transportation:

The measure of intermediate purchases input is constructed as a Tornqvist index of separate quantities of materials, services, fuels, and electricity consumed by each industry. To avoid double counting, estimates of materials purchased from other establishments within the industry are subtracted from gross materials costs. Nominal values of materials, fuels, and electricity and quantities of electricity consumed by each industry are obtained from economic censuses and annual surveys of the Bureau of the Census, U.S. Department of Commerce. Purchased business services are estimated using benchmark input-output tables and other annual industry data from the Bureau of Economic Analysis, U.S. Department of Commerce.

For materials, fuels, and purchased services, quantities are derived by deflating current-dollar values with appropriate price deflators. Aggregate materials and purchased services deflators are constructed for each industry by combining detailed producer price indexes and import price indexes from BLS using weights based on detailed commodity or services consumed from the BEA benchmark input-output tables. An aggregate fuels deflator for each industry is constructed by combining producer price indexes for individual fuel categories with weights based on the industry's detailed fuel expenditures from the U.S. Department of Energy.

Energy

For the 18 3-digit NAICS manufacturing industries:

Intermediate inputs (energy, materials, and purchased business services) are obtained from BEA based on BEA annual input-output tables. Tornqvist indexes of each of these three input classes are derived at the 3-digit NAICS level and then aggregated to total manufacturing.

Materials

For the 18 3-digit NAICS manufacturing industries:

Nonenergy materials input represents all commodity inputs exclusive of fuel (electricity, fuel oil, coal, natural gas, and other miscellaneous fuels) but inclusive of fuel-type inputs used as raw materials in a manufacturing process, such as crude petroleum used by the refining industry.  In addition to raw and processed materials, these measures include all incidental commodity inputs such as office supplies, vehicle parts bought for maintenance, and small tools, if these are allowable as current costs for computing business taxes.

For a more complete discussion, please refer to the article "Multifactor Productivity in U.S. Manufacturing," by William Gullickson, Monthly Labor Review, July 1995, pp. 13-27.PDF

For the 4-digit NAICS industries: Materials input is derived from cost of materials data from the Bureau of the Census. Estimates of materials purchased from establishments in the same industry are subtracted. Detailed BLS PPIs are aggregated to produce a deflator to convert materials costs to constant dollars.

Purchased Business Services

For the 18 3-digit NAICS manufacturing industries:

Purchased business services consist of the following nine types: communications; finance and insurance; real estate rental; hotel services; repair services; business services, including equipment rental, engineering and technical services, and advertising; vehicle repair; medical and educational services; and purchases from government enterprises.  These services are estimated from published input-output tables.  The general approach to these estimates is to take service shares in the value of production from annual input-output tables at the greatest possible level of detail; to obtain service costs by multiplying these shares by the value of production as given in the Census of Manufactures or the Annual Survey of Manufactures; and to deflate these current cost estimates.  Prices from many service inputs are available from the BLS price program, from the National Income and Product Accounts, or from private sources.

For a more complete discussion, please refer to the article "Multifactor Productivity in U.S. Manufacturing," by William Gullickson, Monthly Labor Review, July 1995, pp. 13-27.PDF

Foreign Country Data

Multifactor productivity measures for France and Germany are constructed using data from L'institut National de la Statistique et des Etudes Economiques (France) and Statistiches Bundesamt (Germany), and other sources.  The Foreign Labor Statistics web-page contains further information on these measures.

 

Reference period

  • Calendar year.

Methodology

The estimation procedures used in constructing the underlying data series and the various multifactor productivity measures are described in the BLS Handbook of Methods, Bulletin 2490, April 1997.

"Productivity Measures: Business Sector and Major Subsectors," Chapter 10 of the BLS Handbook of Methods, pp. 89-102, pertains to multifactor productivity measures for the private business, private nonfarm business, aggregate manufacturing, and manufacturing industries.

"Industry Productivity Measures," Chapter 11 of the BLS Handbook of Methods, pp. 103-109, pertains to multifactor productivity measures for detailed industries.

"Foreign Labor Statistics," Chapter 12 of the BLS Handbook of Methods, pp. 110-121, pertains to internationally comparable multifactor productivity measures for the manufacturing sectors of the United States, France, and Germany.

The BLS Handbook of Methods is available at a cost of $20.00 from the U.S. General Printing Office and may be ordered by contacting the GPO by mail or phone (202-512-1800) with your request.  The GPO stock number for this bulletin is 029-001-03265-0.

The mailing address is:
Superintendent of Documents
P.O. Box 371954
Pittsburgh, PA
15250-7954

Research

Labor

Workers differ in their educational attainment and work experience, and both of these factors are believed to contribute to productivity growth.  Average levels of educational attainment and work experience have shifted over the past 50 years, as workers have generally become more educated and unusually large cohorts associated with the "baby boom" generation have entered the work force.  These shifts in the composition of the work force have added about 0.2% per year to productivity growth between 1948 and 1998, as reported in the May 6, 1998 news release Multifactor Productivity Trends Labor Composition and U.S. Productivity Growth, 1948-90, BLS Bulletin 2426, December 1993, provides further information on labor composition effects.

Current research seeks to strengthen and extend these measures with longitudinal microdata from the Survey of Income and Program Participation.  This survey collects annual data on total work experience, which have been shown to dominate the work experience proxies used in earlier research.  The research focuses on incorporation of earnings equation selection bias correction factors, derived from conventional labor supply equations, into the regular procedure with which the index is constructed. Based on this research, labor composition measures will be updated and its impact on productivity growth will be analyzed.

Capital

Research in this area includes an examination of the treatment of inventories in a growth accounting framework, investigation of the role of inventories as an input and the measurement of their contribution to output and productivity.

Research and Development

Investment in research and development (R&D) benefits not only the company undertaking the research but also other firms in the same industry and firms in other industries which purchase research intensive capital or materials. Because R&D benefits firms that did not pay for the research, R&D has a social return not captured by traditional productivity measures.  The Impact of Research and Development on Productivity Growth, BLS Bulletin 2331, published in December 1989, investigated the direct effect of R&D on firms within the same industry and found a social direct return of 30 percent and a direct effect on multifactor productivity of 0.15 percent per year.

Current research investigates the indirect effect of R&D on purchasers of research intensive equipment and materials.  The project will measure the stocks of R&D embodied within purchases of capital and materials and estimate their impact on productivity.  Social indirect rates of return are determined from a variety of methods and the impact of indirect R&D on measured productivity will be determined.

Disequilibrium Effects

The standard productivity model assumes perfect competition and constant returns to scale.  Completed research has shown how to modify the standard growth accounting formula for imperfect competition and non-constant returns to scale.

Research is underway to econometrically estimate a cost function for manufacturing and derive annual measures of the degree of scale and imperfect competition.  These additional parameters will then be used to measure the impact of imperfect competition and returns to scale on productivity measures.  An additional result will be measures of capacity utilization based on differences between short run marginal and average costs.

Infrastructure

Productivity measures the relationship between output and paid inputs.  However, some inputs such as R&D and public infrastructure contribute to output even though they are not paid for by the firm directly.  Recent academic research has produced widely differing estimates of the impact of public infrastructure (highways, airports, sewers, and related government investment) on productivity.  Because government spending can have a stimulative effect on the general economy, state or national models of infrastructure may be misleading.

This research will develop public infrastructure stocks by county for the 1970s and 1980s from the Census of Governments.  In turn these data will augment a cost function for manufacturing at the county level.  Fixed effects models will also be estimated.  The social return to infrastructure and its impact on productivity will be measured.

Publications

On the Internet

News Releases:

Related Documents:

Bulletins and staff papers:

  • Archive of MLR Articles on Productivity and Technology.
  • "Multifactor Productivity for Three-digit SIC Manufacturing Industries, 1990-99," (PDF  150K) Report 956, January 2002.
  • BLS Handbook of Methods, Bulletin 2490, April 1997.
  • "Productivity Measures: Business Sector and Major Subsectors," Chapter 10 of the BLS Handbook of Methods, BLS Bulletin 2490, April 1997, pp. 89-102.
  • "Industry Productivity Measures," Chapter 11 of the BLS Handbook of Methods, BLS Bulletin 2490, April 1997, pp. 103-109.
  • "Foreign Labor Statistics," Chapter 12 of the BLS Handbook of Methods, BLS Bulletin 2490, April 1997, pp. 110-121.
  • "The BLS Productivity Measurement Program," PDF (95K), by Edwin R. Dean and Michael J. Harper, Discussion Paper presented at the Conference on Research in Income and Wealth:  New Directions in Productivity Research, March 20-21, 1998.  How to view a PDF file.
  • "Hours at Work Survey, 1999," PDF (12K), by Aklilu Zegeye and Larry Rosenblum. Brief description of the Bureau of Labor Statistics Hours at Work Survey for 1998.  How to view a PDF file.
  • "Productivity Measurement with Changing-Weight Indexes of Outputs and Inputs," PDF (131K), by Edwin R. Dean, Michael J. Harper, and Mark S. Sherwood.  Discussion paper presented at the OECD Expert Workshop on Productivity: International Comparison and Measurement Issues, May 2-3, 1996.  How to view a PDF file.
  • "Measurement of Productivity Growth in U.S. Manufacturing," PDF (123K), by William Gullickson, Monthly Labor Review, July 1995, pp. 13-27.  How to view a PDF file.

Other Publication Sources

Periodic review articles and special analytical articles in the Monthly Labor Review, including:

  • "Difficulties in the Measurement of Service Outputs," PDF (654K), by Mark Sherwood, Monthly Labor Review, March 1994, pp.11-19.
  • “Multifactor productivity change in the air transportation industry” PDF (73 KB), by John Duke and Victor Torres, Monthly Labor Review, March 2005, pp.32-45.
  • "Multifactor productivity trends in manufacturing industries, 1987-96," PDF (91K), by Ziaul Z. Ahmed and Patricia S. Wilder, Monthly Labor Review, June 2001, pp.3-11.
  • "Multifactor Productivity in the Utility Services Industries," PDF (1094K), by John L. Glaser, Monthly Labor Review, May 1993, pp. 34-48.
  • "Hours at Work: a New Base for BLS Productivity Statistics," PDF (594K), by Mary Jablonski, Kent Kunze, and Phyllis Flohr Otto, Monthly Labor Review, February, 1990, pp. 17-24.

Unpublished measures—available on request—containing information on the components of the labor, capital, and output measures prepared as part of the multifactor program.

 

Last Modified Date: August 21, 2007