Update and Revision History
Indices for international agricultural total factor productivity were first published on the ERS website in November 2013, and covered the period from 1961 to 2010. In October 2014, an updated version was posted covering 1961–2011. In October 2021, a new and substantially revised TFP series was published covering the years from 1961 to 2019. In October 2022, the data were updated and extended to 2020. This section briefly describes the updates to the international agricultural TFP indexes and details the various changes that have been introduced since the initial 2013 database was published.
The October 2022 update extended the data series to 2020. Data from previous years were also updated using the latest available revisions from original data sources.
The October 2021 update introduced major changes to output, input, and TFP measurement: (1) the definition of agricultural output was expanded to include products for aquaculture in addition to crop and animal products; (2) a new FAO measure of agricultural capital stock was adopted for years since 1995; (3) a new set of land quality weights for irrigated areas was adopted to construct a measure of quality-adjusted agricultural land area; (4) definitions of world regions were modified; (5) selected modifications were made for agricultural labor and land estimates for a few countries, mostly for pre-1990 years; and (6) output, input, and TFP indices were rebased to 2015 (i.e., they equal 100 in 2015).
On November 21, 2019, the collection of data files in the International Agricultural Productivity data product were revised to correct an error in the reported gross agricultural output for "Ethiopia, former" for the years 2011-16. Estimates of 2011-16 agricultural output and derived total factor productivity were revised for "Ethiopia, former," and the regions of "SSA, Horn," "Africa, Sub-Sahara," "Developing Countries," "Low Income Countries," and "World." The charts available in the Summary Findings were also revised where needed; at the most aggregated level, for example, average annual global agricultural output growth over 2001-16 is now 2.45 percent, not 2.47 percent per year as originally reported.
This update uses ILOSTAT modeled estimates of the agricultural labor force for years since 1990, except for Argentina. For years prior to 1991, annual growth rates in agricultural labor from previously published FAO data are used to extrapolate the ILO series back to 1961. For Argentina, agricultural labor is from the 10-Sector Database maintained by the GGDC (Timmer et al., 2015). The GGDC estimates for agricultural labor in Argentina are reported annually through 2011, and are extrapolated for more recent years using the 2008-11 average annual growth rate from this series.
The October 2019 update uses exclusively the International Fertilizer Association IFADATA database for fertilizer consumption (previously, we combined data from IFA and FAO). For small countries, IFADATA reports totals for "other" countries in Africa, East Asia, Oceania, West Asia, and Latina America and the Caribbean. To estimate fertilizer consumption for these small countries, we allocate the "other" total in proportion to the country’s share of crop area harvested for that group of countries.
The October 2018 update reported the annual TFP series using a base year (the year in which the index has a value of 100) of 2005, i.e., TFP is set to 100 in 2005 for every country and region for which TFP is calculated. For each country/region, the value of the agricultural TFP for every other year of the index is in relation to TFP in the base year. Thus, if for a particular country TFP in 2015 has a value of 120, then TFP in that year is 20 percent higher in 2015 compared with 2005. Previous versions provided two indices, one with a base year of 1992 and one with a base year of 2005. The index with a base of 1992 is no longer reported.
The October, 2018 update changed the measure of aggregated animal feed from metric tons of dry matter to megacalories (mcal) of energy. Although the two measures are highly correlated, measuring feed in terms of its energy content provides a better measure of feed quality. The energy content of each feed type is from the "United States-Canadian Tables of Feed Composition: Nutritional Data for United States and Canadian Feeds, Third Edition," National Research Council, National Academies Press (1982).
The October, 2017 update no longer used the Hodrick-Prescott filter to smooth the output series. Instead, the agricultural output index is now identical to the FAO index of gross agricultural output.
The October, 2017 update introduced new input cost shares estimated for Russia from Rada, Liefert, and Liefert (2017) and applies them to Belarus, Kazakhstan, Moldova, Russia, Ukraine, and the Baltic States for the post-1991 periods.
This update reported indices of output, input and total factor productivity using base years of 1991 and 2014 (in the base year, an index takes the value of 100). Previous versions used base years of 1961 and 1992. Note that the choice of base year is arbitrary, and has no effect on the growth rate of the series.
On January 5, 2017, the file "AgTFPcountrygeographicgroups.xlsx" was replaced to correct an error in the amount of agricultural land for SE Asia.
The October, 2016 update introduced a new model for extrapolating farm machinery stocks to recent years for countries not reporting such data since the last agricultural census. First, for the United States, Canada, Brazil, Argentina, Mexico, South Africa, and European countries, farm machinery stocks are augmented by the number of new farm machines sold, assuming an average 15-year useful lifespan for farm machinery. Data on annual sales of new farm tractors and combine-harvesters during 1991-2013 were collected from farm machinery manufacturers. For other countries, an econometric model was estimated to predict the annual rate of change in farm-held machinery stocks since the latest available census or survey data on farm machinery stocks. The econometric model is based on the Kislev and Peterson (1982) model of farm machinery adoption and farm size. Kislev and Peterson (1982) hypothesized that as non-farm wages rose, farm labor would be induced to migrate to the non-farm sector. This would stimulate farm consolidation and mechanization to replace the labor leaving farms. Thus, farm mechanization would be correlated with non-farm wages and average farm size. While the Kislev-Peterson model was developed in specific reference to the United States, in a comparative historical assessment of agricultural mechanization, Binswanger (1986) found a "remarkable similarly in the early mechanization experiences of developed and developing countries."
This update revised the method for estimating agricultural labor for Nigeria. Nigeria has the largest economy and is the largest agricultural producer in Sub-Saharan Africa, although socio-economic data for this country, particularly its population and labor force, remain subject to considerable uncertainty. In previous versions, Nigeria agricultural labor force estimates are from Fuglie and Rada (2013), who used FAO data (2006 version) for 1961-1966 and then extrapolated them to the present assuming a 2 percent annual growth rate (roughly the rate for the rest of Sub-Saharan Africa). The new method uses national census and survey data to determine the share of the labor force in agriculture over time, and multiplies this share by the ILO estimate of the total labor force to get the size of the agricultural labor force.
The October, 2015 update corrected an error in FAO data on agricultural land in New Zealand prior to 2002. The agricultural land series for New Zealand for 1961-2002 are derived from Statistics New Zealand (2003).
This update introduced input cost shares from Rada (2016) for India in the post-1991 periods that are applied to all South Asian countries.
The October, 2015 update included an explicit measure of total animal feed used as an input in livestock production. Previous versions of the database assumed that animal feed grew at the same rate of the size of the global livestock herd (measured in cattle-equivalent units). The new estimate uses actual quantities of animal feed from FAO Commodity Balance Sheets, which provide annual data from 1961 to 2011 (except for former Soviet Socialist Republics (SSRs), for which data are available from 1992 to 2011), on quantities of all types of feed except forage and silage. Total feed quantity is the sum of all crops, crop processing residues (like oilseed meals, sugar, molasses, and bran from flour and grain milling), animal and fish products (including meat, fish, fish meals and whey) in metric tons of dry matter. The dry matter content of each feed type is from the "United States-Canadian Tables of Feed Composition: Nutritional Data for United States and Canadian Feeds, Third Edition," National Research Council, National Academies Press (1982). Dry matter is calculated on the basis of 89 percent dry matter for grain, which is the standard dry matter content of marketed grain. For SSRs prior to 1992, total USSR feed use is apportioned amongst them according to the proportion of total USSR livestock (in cattle-equivalents) in each SSR. Animal feed inputs are extrapolated to 2012 for each country using the average growing rate in animal feed from the previous three years in that country.
The October, 2015 update revised estimates of machinery stocks for recent years by adding data on the number of tractors and combine-harvesters held on farms from national statistical sources. Historical statistics on farm stocks of tractors and combine-harvesters were collected for Bangladesh, China, Europe, India, Japan, Russia, and the United States. These countries account for more than 70 percent of farm machinery stocks globally. For other countries, estimates of farm machinery stocks were unchanged.
The October, 2014 update revised the method for estimating machinery stocks. As FAO reports farm machinery stocks through no later than 2009 (and for some countries the series ends even earlier), extrapolation methods are used to estimate farm machinery stocks into the future. The original 2013 data release assumed the same level of machinery stocks in 2010 as in 2009 or the last year for which estimates were available. The 2014 update assumes that machinery stocks grew at the same rate as the ratio of agricultural land to farm workers. This procedure is designed to reflect machinery-labor substitution taking place in some countries as labor leaves the agricultural sector.
This update reassigned Pacific island states from the Oceania Region to the Asia Region.
The original international agricultural TFP data product was released in November, 2013 and covered the period 1961-2010.
See References for a complete list of citations mentioned.