ERS Charts of Note
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Monday, April 18, 2022
Agricultural output in the United States nearly tripled between 1948 and 2017, with average annual output growth at 1.53 percent. While reduction of labor hours worked has contributed negatively, changes in labor quality have contributed positively to output growth over the years. Labor quality includes shifts in composition of demographic attributes, such as gender, age, educational attainment, employment type and other factors. ERS researchers group the study period into 12 sub-periods in accordance with U.S. economic business cycles (from peak to peak). Most of the contraction in total hours worked occurred between 1948 and 1969, during the expansionary period after World War II. By the 2007–17 economic business cycle, the decline in labor hours had its lowest negative effect on output growth, -0.16 percentage points. ERS researchers found that total labor quality had a positive effect on output growth in all economic business cycles except the 1979-81 period. The effects of labor quality on agricultural output growth were especially prominent before 1969. It accounted for nearly 25 percent of total output growth per year in the 1948–53, 1953–57, and 1960–66 subperiods, and 14 percent of annual output growth in the 1966-69 subperiod. Except for the period immediately after WWII, the major source of labor quality changes was an increase in educational attainment among farmworkers. On average, the increase in educational attainment accounted for more than 90 percent of the changes in labor quality between 1948 and 2017. Nevertheless, since 1969, the rise in educational attainment has slowed, and the overall influence of labor quality on output growth has diminished. This chart is drawn from the USDA, Economic Research Service report “Farm Labor, Human Capital, and Agricultural Productivity in the United States,” published Feb. 15, 2022.
Tuesday, February 22, 2022
Organic dairy farms must follow a variety of USDA regulations to obtain certification and maintain their organic status. For example, they have to use organic grains and feed supplements, and they mostly rely on pasture-based feeding, which makes them more vulnerable to weather shocks such as drought or sudden and intense storms. These challenges mean productivity on organic dairy farms grows at a slower rate than on operations using conventional processes. Productivity is measured as total factor productivity (TFP), the ratio of the total amount of goods (in this case, milk) produced relative to all the inputs—such as labor, fertilizer, and other costs—used to produce those goods. USDA, Economic Research Service (ERS) researchers studied the difference in TFP growth between organic and conventional farms using data from organic dairy farms between 2005–16 and from conventional dairy farms between 2000–16. TFP grew at an annual rate of 0.66 percent for organic dairy farms compared with 2.51 percent among conventional dairy operations. Both organic and conventional farms saw productivity growth due to technological progress such as advanced equipment and improved genetics. While weather-related feed factors reduced productivity for organic farms, they contributed to a productivity growth for conventional dairy farms. Technical efficiency increased productivity slightly on organic farms, but reduced productivity on conventional farms, while scale-and-mix efficiency reduced productivity for both types of farms. This chart was included in the ERS report Sources, Trends, and Drivers of U.S. Dairy Productivity and Efficiency, published in February 2022.
Wednesday, February 16, 2022
Agricultural output in the United States nearly tripled between 1948 and 2017 even as the amount of labor hours-worked declined by more than 80 percent. These opposing trends resulted in an increase in labor productivity growth in the U.S. farm sector. Labor productivity—calculated as average output per unit of labor input—is a popular measure for understanding economic growth. According to USDA, Economic Research Service (ERS) estimates, agricultural output per worker grew by 16 times from 1948 through 2017. At the same time, agricultural output per hour worked grew even faster, by 17 times, implying that average hours worked per worker declined. Labor productivity estimates can vary based on different ways labor is measured. One factor in the increased labor productivity is the quality of labor, measured by attributes such as age, gender, and the highest level of education a worker has reached. Because these attributes may affect worker performance, ERS researchers accounted for labor quality changes in analyzing farm labor productivity. When labor quality changes since 1948 were accounted for, labor productivity grew at a slower rate than those based simply on hours worked or employment. The reason is because labor quality is treated as a part of labor input instead of productivity. This implies that changes in labor quality, such as improvements in education, account for much of the change in labor productivity over the last seven decades. ERS researchers estimate that changes to farm worker attributes accounted for about 13 percent of growth in hourly based annual labor productivity during the time studied. This chart in included in the ERS report Farm Labor, Human Capital, and Agricultural Productivity in the United States, published Feb. 15, 2022.
Tuesday, January 18, 2022
In 2020, most of the values of cotton (62 percent), dairy (73 percent), and specialty crops (57 percent) were produced on large-scale family farms. USDA defines a family farm as one in which the principal operator and related family own the majority of the assets used in the operation. Large-scale family farms are those with an annual gross cash farm income of $1 million or more. However, small family farms produced the bulk of hay production (59 percent) and poultry and egg output (49 percent) in 2020. Poultry operations are often classified as “small” because most output is under a production contract arrangement, with a contractor paying a fee to a farmer who raises poultry to maturity. Additionally, more than one-quarter of beef production occurred on small family farms that generally have cow/calf operations. Another 42 percent of beef production occurred on large-scale family farms, which are more likely to operate feedlots. Midsize family farms production ranges from 8 to almost 30 percent of value of production. Nonfamily farms produce the smallest share of the value of production for most commodities. Of all the commodities, nonfamily farms contribute the most to specialty crop production at 27 percent. This chart is found in the Economic Research Service report, America’s Diverse Family Farms: 2021 Edition, released December 2021.
Wednesday, January 12, 2022
Since the 1960s, global agricultural output by volume has increased at an average annual rate of 2.3 percent, fluctuating between 2 and 3 percent on a decade-to-decade basis. In the latest decade (2011–19), the global output of total crop, animal, and aquaculture commodities grew an average rate of 2.08 percent per year. Several factors contribute to output growth, including expansion of agricultural land, extension of irrigation to existing cropland, the intensification of input use (more labor, capital, and material inputs per acre), and total factor productivity (TFP), a measure of the contribution of technological and efficiency improvements in the farm sector. Before the 1990s, most output growth came from increases in input use, including expansion of land, irrigation, and intensification of other inputs. Since the 1990s, growth in TFP, rather than growth in inputs, accounted for most of the growth in world agriculture output. From 2011 to 2019, TFP globally grew at an annual rate of 1.31 percent, accounting for nearly two-thirds of output growth. This chart comes from the USDA, Economic Research Service data product International Agricultural Productivity, updated in October 2021.
Friday, December 10, 2021
Total factor productivity (TFP) growth reflects the rate of technological and efficiency improvements in the agricultural sector and productivity growth varies across countries. TFP measures the amount of agricultural output produced from the combined set of land, labor, capital, and material resources employed in the production process. Agricultural TFP grew most rapidly (at more than 2 percent on average) in the dark green-colored countries and most slowly (or not at all) in the light green-colored countries. National policies and institutions, especially those that promote innovation and technical change, play a significant role in driving TFP growth in agriculture. Strengthening the capacity of national agricultural research and extension systems to develop and deliver new agricultural technologies to farmers has been a critical factor in raising agricultural productivity. Information from the International Agricultural Productivity data product and related ERS research show that that Brazil and India’s TFP growth can be attributed to long-term investments in agricultural research. China’s TFP growth can be attributed to investments in research and institutional and economic reforms. In contrast, Russia’s low rate of agricultural TFP growth is attributed to inefficiencies under a planned economy (until 1991) followed by economic disruptions that accompanied its transition to a market economy. Under-investment in agricultural research and extension and poor market infrastructure remain important barriers to stimulating agricultural productivity growth in Sub-Saharan Africa. This data can be found in the International Agricultural Productivity data product, last updated in October 2021.
Monday, July 12, 2021
Raising the productivity of existing agricultural resources—rather than bringing new resources into production—has become the major source of growth in world agriculture. Farm productivity is measured by total factor productivity (TFP), an index that takes into account the land, labor, capital, and material resources employed in farm production and compares them with the total amount of crop and livestock output. If total output is growing faster than total inputs, then the total productivity of the factors of production (i.e., total factor productivity) is increasing. Using the latest available data through 2016, agricultural productivity has risen steadily in most industrialized countries at between 1 and 2 percent a year since at least the 1970s. Since the 1990s, many developing countries as well as transition economies that belonged to the former Soviet bloc also have increased their agricultural productivity. Long-term research investments to develop new technologies have been especially important to sustaining higher agricultural TFP growth rates in large, rapidly developing countries such as Brazil and India. Institutional and economic reforms, combined with technological changes, have led to significant benefits for Chinese agriculture. Additionally, Russian agriculture rebounded after the early 1990s economic transition from a planned to a market-based economy, and the southern region of the country achieved notable productivity improvement. In contrast, under-investment in agricultural research remains an important barrier to stimulating agricultural productivity growth in Sub-Saharan Africa. This chart appears in USDA, Economic Research Service data product for International Agricultural Productivity, updated November 2019.
Monday, November 16, 2020
In 2019, Wisconsin’s production of fluid milk was second only to California’s. According to data from USDA’s National Agricultural Statistics Service, Wisconsin generated 30.6 billion pounds of milk that year, with milk sales totaling $5 billion. In recent years, Wisconsin dairy farms have been exposed to substantial weather volatility characterized by frequent droughts, storms, and temperature extremes (both hot and cold). This has resulted in considerable fluctuations in dairy productivity. Researchers from the Economic Research Service (ERS) among others, found that total factor productivity (TFP), which measures the rate of growth in total output (aggregate milk produced) relative to the rate of growth in total inputs (such as the number of cows, farm labor, feed, and machinery), increased at an average annual rate of 2.16 percent for Wisconsin dairy farms between 1996 and 2012. This increase was primarily driven, at an annual rate of 1.91 percent, by technological progress—such as improved herd genetics, advanced feed formulations, and improvements in milking and feed handling equipment. However, trends in rainfall and temperature variation were responsible for a 0.32 percent annual decline in the productivity of Wisconsin dairy farms during the same period. For example, an average increase in temperature of 1.5 degrees Fahrenheit reduced milk output for the average Wisconsin dairy farm by 20.1 metric tons per year. This is equivalent to reducing the herd size of the average farm by 1.6 cows every year. This chart appears in ERS’s October 2020 Amber Waves finding, “Climatic Trends Dampened Recent Productivity Growth on Wisconsin Dairy Farms.”
Wednesday, August 26, 2020
The total output—including livestock, crops, and other farm related outputs—produced by U.S. farms nearly tripled between 1948 and 2017, growing at an average annual rate of 1.53 percent. This output growth was primarily attributable to increased productivity, which grew at an average of 1.46 percent per year. Total inputs—including capital, land, labor, and intermediate goods—increased by 0.07 percent annually, by comparison. Though total input use grew slowly during this period, its composition shifted considerably. The use of intermediate goods (such as feed, seeds, and chemicals) increased by more than 130 percent, while agricultural labor declined by 76 percent and the amount of land devoted to agriculture was down by more than 25 percent. The continuing growth in intermediate goods contributed 0.58 percentage points per year to output growth, the highest among all inputs (capital, labor, and intermediate goods). However, the contribution of intermediate goods to output growth has been small (even negative in some years) since 1981. Over the long-term, productivity growth has been the major driver of agricultural growth. Productivity growth—spurred by innovations in animal and crop genetics, chemicals, equipment, and farm organization through research—is the only factor that contributed positively to agricultural growth in all sub-periods (measured from peak to peak between business cycles) since 1948. This chart appears in the July 2020 Amber Waves article, “Productivity Is the Major Driver of U.S. Farm Sector’s Economic Growth.”
Monday, May 11, 2020
U.S. regulations on antibiotic use in food animal production have focused on antibiotics important for human disease treatment, which the Food and Drug Administration (FDA) terms “medically important.” If current human antibiotics lose efficacy and new ones are not developed, the ability to treat human infections may be hindered. In 2017, FDA policies ended the use of medically important antibiotics for growth promotion in food animals. Antibiotics deemed “currently not medically important” are not used to treat human illnesses and can still be used for animal growth promotion. Other uses of medically important antibiotics in food animal production require veterinarian oversight. These policies follow earlier actions in the European Union (EU) banning medically important antibiotics for growth promotion. Most new antibiotic approvals for food animals have been generic drugs that are also used for humans. Between 1992 and 2015, about 70 percent of antibiotics were considered medically important. This suggests that animal pharmaceutical companies are increasingly developing generic antibiotics for food animals, not new varieties of antibiotics. Although new approvals for non-medically important, non-generic antibiotics for food animals declined, they still averaged about 1.3 per year in 2015. This chart appears in the ERS report, The U.S. and EU Animal Pharmaceutical Industries in the Age of Antibiotic Resistance, released May 2019.
Friday, April 3, 2020
The growth rate of the world’s agricultural output has varied over the decades. Output growth slowed in the 1970s and 1980s, but then accelerated in the 1990s and 2000s. In the latest period for which estimates are available (2001-16), global output of total crop and livestock commodities grew by an average rate of 2.45 percent per year. The different bar colors in the chart show the sources of this output growth. In the decades prior to 1990, most output growth came about from intensification of input use (more labor, capital, and material inputs per acre). Bringing new land into agriculture production and extending irrigation to existing agricultural land were also important sources of growth. During the periods of 1991-2000 and 2001-16, however, the rate of growth in input use significantly slowed. Instead, improvements in agricultural productivity—getting more output from existing resources—drove global output growth. Total factor productivity (TFP) grew from the adoption of new technologies, management practices, and other efficiency improvements in farming around the world. Between 2001 and 2016, TFP accounted for 77 percent of the total growth in agricultural output worldwide. This chart appears in the Economic Research Service topic page for International Agricultural Productivity Summary Findings, updated November 2019.
Wednesday, February 19, 2020
Technological developments in agriculture have been influential in driving changes in the farm sector. Innovations in animal and crop genetics, chemicals, equipment, and farm organization have enabled continuing output growth without adding much to inputs (including land, labor, machinery, and intermediate goods). As a result, even as the amount of land and labor used in farming declined, total farm output nearly tripled between 1948 and 2017. During this period, agricultural output grew at an average annual rate of 1.53 percent, compared to 0.07 percent for total farm inputs. Output growth was largely driven by the growth in agricultural productivity, as measured by total factor productivity (TFP)—the difference between the growth of aggregate output and growth of aggregate inputs. Between 1948 and 2017, TFP grew at an average annual rate of 1.46 percent. In the short term, TFP estimates can fluctuate from time to time—reflecting transitive events, such as bad weather or oil shocks—but it usually recovers and returns to its long-term trend growth, as has happened in recent years. This chart appears in the ERS data product, Agricultural Productivity in the U.S., updated January 2020.
Friday, February 14, 2020
At $64.7 billion, specialty crops comprised one-third of U.S. crop receipts and one-sixth of receipts for all agricultural products in 2017. Many specialty crops are labor-intensive in production, harvesting, or processing. For example, harvest often requires workers to accurately distinguish ripe and unripe fruits and vegetables and gently pick, sort, or package the fruit or vegetable by hand without damage. A long-term decline in the supply of farm labor in the U.S. has encouraged producers to select less labor-intensive crops, invest in labor-saving technologies, and develop strategies to increase labor productivity. A number of USDA programs support the development and use of automation or mechanization in the production and processing of U.S. specialty crops. From 2008-2018 these programs in the Agricultural Marketing Service (AMS), the Agricultural Research Service (ARS), and the National Institute of Food and Agriculture (NIFA) funded $287.7 million toward 213 projects to develop and enhance the use of automation or mechanization in specialty crop production and processing. Projects covered a broad spectrum of technologies, including job aid and machinery automation; machine learning and data analysis; mechanical harvesting and processing; precision agriculture; remote sensing and drones; and sensors. Each of the USDA programs are designed differently to achieve unique objectives, although each program addresses the development and use of automation or mechanization in specialty crops in some form. The data in this chart are available in the February 2020 ERS report, Developing Automation and Mechanization for Specialty Crops: A Review of U.S. Department of Agriculture Programs.
Monday, December 16, 2019
Many antibiotics developed for use in animal production are “cast-offs” from products originally intended to be marketed to humans. Therefore, the decline in the development of new human antibiotics suggests there may a similar decline in the development of new antibiotics for food animal production. The share of food-animal antibiotics as a portion of all veterinary drug approvals has declined from 62 percent in 1992-94 to 40 percent in 2013-15. The decline reflects increasing development of new animal drugs approved for companion animals, from 30 percent of all approvals in 1992-94 to 47 percent in 2013-15. Given the overall decline in the number of all animal drug approvals between 1992 and 2015, the decline in the share of food-animal antibiotics approvals also reflects a decline in the number of approvals for such drugs. This chart appears in the ERS report, The U.S. and EU Animal Pharmaceutical Industries in the Age of Antibiotic Resistance, released May 2019. See also the Amber Waves article, “Developing Alternatives to Antibiotics Used in Food Animal Production,” published in May 2019.
Wednesday, December 4, 2019
One way of comparing research and development (R&D) investment across countries is to measure R&D spending relative to the size of the economy, or as a percentage of Gross Domestic Product (GDP). While the United States spends more on public agricultural R&D than other high-income countries, U.S. expenditures relative to the size of its agricultural sector have been about average. Over time, agricultural R&D spending has tended to rise as a percentage of agricultural GDP in virtually all countries. This tendency reflects the greater technological sophistication of agriculture, as well as the broadening of research agendas beyond production agriculture to include more emphasis on various societal issues, including food safety, rural development, and the environment. In the United States, public spending on agricultural R&D as a percentage of GDP peaked in the mid-2000s at about 3.5 percent of agricultural GDP but significantly declined since 2009. By 2013, public spending fell to 2 percent of agricultural GDP. U.S. agricultural research intensity is now below average for high-income countries. Leading regions, such as Northwest Europe and high-income Asia, have agricultural R&D spending of around 4.5 percent of agricultural GDP. Public agricultural research intensities also leveled off or even fell in the agricultural-exporting countries of Canada, Australia, and New Zealand. Research intensities in Southern European and Mediterranean countries and in Central European countries have been consistently lower than those in other high-income countries. This chart appears in the ERS report, Agricultural Research Investment and Policy Reform in High-Income Countries, released May 2018.
Friday, October 11, 2019
Recent ERS research examined productivity trends in the Heartland region, which includes all of Iowa, Illinois, and Indiana, and parts of Minnesota, South Dakota, Nebraska, Missouri, Kentucky, and Ohio. Findings show that the smallest crop farms (less than 100 acres) fell further behind larger farms in terms of productivity between 1982 and 2012. Total factor productivity (TFP)—a measure of the quantity of output produced relative to the quantity of inputs used—grew at similar rates across farm-size classes except for the smallest, which had slower growth rates. (However, data for 2012 reflects a severe drought in the Heartland region that year and so does not follow historical trend lines.) While the TFP for farms in the four largest size categories increased by 47 to 59 percent between 1982 and 2012, TFP for the smallest farms increased by only 17 percent. Some technological advances in recent decades, such as very large combine harvesters and precision agriculture technologies, were not as advantageous for the smallest farms to adopt due to cost. This may help explain why the farm productivity growth of the smallest farms has lagged behind that of larger operations. This trend has resulted in a deterioration of the competitive position of farms in the smallest size category, and has likely contributed to a decline in their share of total output. This chart appears in the December 2018 Amber Waves feature “Productivity Increases With Farm Size in the Heartland Region.”
Monday, September 9, 2019
U.S. farm output since 1948 has grown by 170 percent. Increases in total factor productivity (TFP), measured as total output per unit of total input, accounted for more than 90 percent of that output growth. However, TFP growth rates fluctuate considerably year-to-year, mostly in response to adverse weather, which can lower productivity estimates. Recent ERS research modeled a future climate-change scenario with an average temperature increase of 2 degrees Celsius (3.6 degrees Fahrenheit) and a 1-inch decrease in average annual precipitation. Results showed that the “TFP gap index”—the difference in total-factor productivity levels between the projected period (2030–40) and the reference period (2000–10)—varies by State. For some States, those climate changes fall within the range of what is historically observed, while for other States they do not, which accounts for regional variation. States in the latter category are projected to experience larger effects. The States experiencing the greatest impacts would include Louisiana and Mississippi in the Delta region; Rhode Island, Delaware, and Connecticut in the Northeast region; Missouri in the Corn Belt region; Florida in the Southeast region; North Dakota in the Northern Plains region; and Oklahoma in the Southern Plains region. This chart appears in the Amber Waves article, “Climate Change Likely to Have Uneven Impacts on Agricultural Productivity,” released August 2019.
Tuesday, July 9, 2019
Historically, public institutions often played a direct role in developing new agricultural technologies and encouraging their commercialization and adoption by farmers. Levels of public investment in research and development (R&D) increased through the early 1980s. However, since then, growth rates in public-sector R&D have been generally low. Until 2003, private-sector investment was comparable to, or moderately higher than, public-sector investment—though growth in private-sector investment had been more variable. After 2003, however, public and private research investments began to diverge rapidly. Total private agricultural and food R&D doubled between 2003 and 2014, while public R&D fell. By 2010, private R&D for agricultural inputs alone surpassed the public level for all agricultural research, which also includes research in areas not directly related to crop and livestock production. Public and private agricultural research efforts are often complementary, rather than competitive. The private sector focuses mainly on R&D related to marketable goods and technologies, with a large share of investments going to the food manufacturing industry, which has little impact on agricultural productivity. The private sector also dominates farm machinery research. On the other hand, public-sector research efforts are more likely to be applied to areas with large social benefits, such as environmental protection, nutrition, and food safety. This chart appears in the ERS data product Agricultural Research Funding in the Public and Private Sectors, updated February 2019.
Monday, June 3, 2019
The human and animal pharmaceutical industries are closely linked, with similar research processes and business structures. However, although animal pharma is a large global presence ($23.9 billion in sales in 2014), human pharma is 42 times larger (nearly $1 trillion in sales in 2014). Because the human pharma market is more lucrative, many drugs are originally explored for use in humans. Human drug innovations historically also have been a source of new products in animal pharma. Conversely, trends in the numbers of new drug approvals in the United States for humans versus animals have diverged over time. Between 1971 and 2015, the number of new nongeneric drug approvals for animal use dropped from 154 to 30 annually, while those for human use climbed from 136 to 392 annually. The higher number of approvals for human drugs reflects the larger size of the human pharma market. This divergence in the numbers of drug approvals may also be driven by changes in the focus of human medicine, which increasingly demands palliative care drugs that have fewer applications in the animal pharmaceutical market. This chart appears in the ERS report, The U.S. and EU Animal Pharmaceutical Industries in the Age of Antibiotic Resistance, released May 30, 2019. See also the Amber Waves article “Developing Alternatives to Antibiotics Used in Food Animal Production,” published in May 2019.
Tuesday, March 19, 2019
Past ERS research on consolidation in the U.S. farm sector has documented a widespread shift in agricultural production to large-scale operations. This structural change has likely been partly driven by productivity advantages enjoyed by larger operations. Recent ERS research examined consolidation trends in the Heartland region—which includes all of Iowa, Illinois, and Indiana, and parts of Minnesota, South Dakota, Nebraska, Missouri, Kentucky, and Ohio. Between 1982 and 2012, the Heartland’s largest crop farms (more than 1,000 acres) increased their share of total production in the region from 17 percent in 1982 to 59 percent in 2012. In contrast, over the same period, the share of total production declined for the four smaller farm size categories. Midsized farms (250–500 acres) experienced the largest decline in market share, falling from about 30 percent in 1982 to 10 percent in 2012. In aggregate, the productivity of crop farms in the Heartland region increased by 64 percent, or 1.5 percent per year, between 1982 and 2012. ERS researchers estimate that about one-sixth of this productivity growth was attributable to the shift in production to larger farms. This chart appears in the December 2018 Amber Waves feature “Productivity Increases With Farm Size in the Heartland Region.”