Update and Revision History
This page compiles updates and revisions to the data as of January 6, 2022.
January 6, 2022
Updated 1948-2019 U.S. productivity statistics were released; we extend the productivity accounts to 2019. Some historical estimates of prices, quantities, and total factor productivity are revised to reflect changes made to data sources, including USDA, Economic Research Service (ERS); USDA, National Agricultural Statistics Service (NASS); U.S. Department of Commerce, Bureau of Economic Analysis (BEA); and U.S. Department of Labor, Bureau of Labor Statistics (BLS).
January 10, 2020
Updated 1948-2017 U.S. productivity statistics were released; we extend the productivity accounts to 2017. There are two major changes with this revision. First, we change the index year from 2005 to 2015, so the implicit quantity measures are in 2015 dollars. Second, we change the way we measure inventory rental price and data sources for data consistency. In addition, historical data are revised when there is a revision in our source data—including the changes made by USDA, National Agricultural Statistics Service (NASS); USDA, Economic Research Service (ERS); U.S. Department of Commerce, Bureau of Economic Analysis (BEA); and U.S. Department of Labor, Bureau of Labor Statistics (BLS).
October 10, 2017
Updated 1948-2015 U.S. productivity statistics were released; we extend the productivity accounts to 2015. Historical data are revised when there is a revision in our source data.
To reflect the changes made by USDA, National Agricultural Statistics Service (NASS); USDA, Economic Research Service (ERS); U.S. Department of Commerce, Bureau of Economic Analysis (BEA); and U.S. Department of Labor, Bureau of Labor Statistics (BLS); some output and input series have been revised as far back as 1948 for consistency. For example, some changes reflect revisions in cash receipts, inventory changes, and production expenses made by NASS and ERS, or labor estimates reported by BEA or BLS.
September 21, 2016
Revisions were made to the "Methods" chapter, content was added to a new "Update and Revision History" chapter, and the chapter "Uses and Publications" was added.
May 9, 2016
Errata: On May 9, 2016, the data file for Table 23. Price indices and implicit quantities of farm outputs and inputs by State, 1960-2004 was reposted to remove a duplication of data. A previous version of this file listed the headings "capital services" and "capital services excluding land" with identical data provided for each. "Capital services excluding land" is the correct heading and those data remain and are correct. The duplicate "capital services" heading and data have been removed.
December 14, 2015
Updated 1948-2013 U.S. productivity statistics were released. Changes made with this revision include data sources and measurement as follows.
To reflect the changes made by our data sources, such as NASS, ERS, BEA, and BLS, some output and input data have been revised back as far as 2000. In addition, methodologies for capital measurement and purchases of livestock have changed with this release, and some input estimates are revised back to 1948 when data are available, for consistency.
Changes in the measurement of labor input were necessitated by the adoption of new sources for data on employment, hours worked, and compensation per hour. Our original data source (the Farm Labor Survey administered by USDA's National Agricultural Statistics Service) was discontinued. The data on self-employed and unpaid family workers are now taken from the decennial Census of Population and the annual Current Population Survey. The National Income and Product Accounts (NIPA) are the source for data on employment, hours worked, and compensation of hired farm workers. The adoption of the new data sources has allowed us to extend our estimates of labor input (and hence productivity) through 2013, but has also required that we revise these series for prior years. In addition, the American Community Survey (ACS), was fully implemented in 2005 by the Census Bureau, is now part of the Decennial Census Program and has replaced the long-form sample questionnaire of the Census of Population. Therefore, we now rely on ACS micro data rather than the decennial Census of Population when developing estimates of labor input.
The share of purchased contract labor services in total production cost has increased over time in US farm production. Since farmers typically contract with labor brokers to assemble crews, there is a scarcity of data on hours worked. Only data on nominal expenditures for contract labor are collected. In order to account for the contribution of contract labor services to output growth, we must construct an appropriate deflator for these expenditures. Since the compensation of contract workers will likely vary with differences in demographic characteristics such as age, experience, gender, and education, we construct a deflator for contract labor using hedonic methods based on data from the National Agricultural Workers Survey.
In this release, purchases of livestock are not included in intermediate input as they were in previous releases. Rather, these animals represent "goods in progress." Acquisitions are, therefore, recorded as additions to stocks, while the cost of livestock purchases is deducted from livestock receipts.
We also introduced changes in the way we measure capital input. There has been a long-standing debate over whether an ex post or ex ante measure of the user cost of capital should be used in growth accounting. In the ex post approach (see, for example, Jorgenson and Griliches, 1967; Christensen and Jorgenson, 1969; Jorgenson, Gollop, and Fraumeni, 1987), it is assumed that the rate of return is equalized across assets. Then this unknown rate can be found by using the condition that the sum of returns across assets (where the return on an asset is the product of its user cost and the flow of services it yields) equals observed gross profits. The alternative ex ante approach (see Coen, 1975; Penson, Hughes, and Nelson, 1977; Diewert, 1980; Romain, Penson, and Lambert, 1987; Ball et al., 2008) employs a rate of return derived from financial market data, together with estimates of expected rather than actual asset price inflation. We adopt the latter approach. The ex ante rate is calculated as the nominal yield on investment grade corporate bonds adjusted for expected, rather than actual, price inflation. We introduce the use of asset-specific rates of price inflation as recommended by Shumway et al. (2014). Earlier (see Ball et al., 1997; 1999), the USDA used a broad measure of inflation, the implicit deflator for gross domestic product, to calculate the real rate of return, based on the theory that expected real rates of return should be equal across all assets.
Our estimates of the stock of land are based on county-level data on land area and value obtained from the Census of Agriculture. Data for the inter-census years are obtained through interpolation using spline functions. The Census reports the value of farm real estate (i.e., land and structures), as opposed to the value of land. Historically, the value of farm real estate was partitioned into components using information from the Agricultural Economics and Land Ownership Survey (AELOS). However, the AELOS was last published in 1999. More recently, we have relied on data from the annual Agricultural Resource Management Survey (ARMS) to partition real estate values into its components.
Pesticides and fertilizer are important intermediate inputs, but their data require adjustment since these inputs have undergone significant changes in input quality over the study period. Since input price and quantity series used in a study of productivity must be denominated in constant-efficiency units, we construct price indexes for fertilizers and pesticides from hedonic regression results. The corresponding quantity indexes are formed implicitly as the ratio of the value of each aggregate to its price index.
Finally, we report price indexes and implicit quantities (i.e., values of expenditures at constant 2005 prices) of the economic aggregates (e.g., output; capital; labor; intermediate goods), see the tab for table 1a. At the State level, these data are reported in panel format (see table 23). They can be used for both time series and cross section analysis.