Graph and download economic data for Total Factor Productivity at Constant National Prices for United States (RTFPNAUSA632NRUG) from 1954 to 2019 about production, price, and USA.

Japan Total Factor Productivity data was reported at 0.175 % in Sep 2018. This records an increase from the previous number of 0.170 % for Mar 2018. Japan Total Factor Productivity data is updated semiannually, averaging 1.032 % from Sep 1983 (Median) to Sep 2018, with 71 observations. The data reached an all-time high of 1.457 % in Mar 1986 and a record low of 0.170 % in Mar 2018. Japan Total Factor Productivity data remains active status in CEIC and is reported by Bank of Japan. The data is categorized under Global Database’s Japan – Table JP.A053: SNA 2008: Potential Growth Rate and Output Gap.

Graph and download economic data for Private Business Sector: Total Factor Productivity (MPU4900013) from 1988 to 2024 about productivity, sector, business, private, rate, and USA.

Labor productivity in the manufacturing sector was the highest in Lebanon in 2019 at about 10.7 U.S. dollars. Countries in conflict and in transition showed smaller employment growth than the rest in the Middle East and North Africa (MENA) region.

The total factor productivity (TFP) in Tunisia in 2013 was the highest in the Middle East and North Africa (MENA) region among firms with above average TFP among the country's income group peers.

Total Factor Productivity (TFP): Business Sector data was reported at 0.457 % in Dec 2024. This records an increase from the previous number of -0.629 % for Sep 2024. Total Factor Productivity (TFP): Business Sector data is updated quarterly, averaging 0.935 % from Jun 1947 (Median) to Dec 2024, with 311 observations. The data reached an all-time high of 16.986 % in Mar 1950 and a record low of -11.695 % in Jun 2020. Total Factor Productivity (TFP): Business Sector data remains active status in CEIC and is reported by Federal Reserve Bank of San Francisco. The data is categorized under Global Database’s United States – Table US.G106: Total Factor Productivity.

Colombia FP: GVA: Mining & Extraction data was reported at 2.592 % in 2023. This records an increase from the previous number of 0.596 % for 2022. Colombia FP: GVA: Mining & Extraction data is updated yearly, averaging 0.596 % from Dec 2020 (Median) to 2023, with 3 observations. The data reached an all-time high of 2.592 % in 2023 and a record low of -15.570 % in 2020. Colombia FP: GVA: Mining & Extraction data remains active status in CEIC and is reported by National Administrative Department of Statistics. The data is categorized under Global Database’s Colombia – Table CO.G075: Total Factor Productivity.

Increasing the efficiency of agricultural production—getting more output from the same amount of resources—is critical for improving food security. To measure the efficiency of agricultural systems, we use total factor productivity (TFP). TFP is an indicator of how efficiently agricultural land, labor, capital, and materials (agricultural inputs) are used to produce a country’s crops and livestock (agricultural output)—it is calculated as the ratio of total agricultural output to total production inputs. When more output is produced from a constant amount of resources, meaning that resources are being used more efficiently, TFP increases. Measures of land and labor productivity—partial factor productivity (PFP) measures—are calculated as the ratio of total output to total agricultural area (land productivity) and to the number of economically active persons in agriculture (labor productivity). Because PFP measures are easy to estimate, they are often used to measure agricultural production performance. These measures normally show higher rates of growth than TFP, because growth in land and labor productivity can result not only from increases in TFP but also from a more intensive use of other inputs (such as fertilizer or machinery). Indicators of both TFP and PFP contribute to the understanding of agricultural systems needed for policy and investment decisions by enabling comparisons across time and across countries and regions. The data file provides estimates of IFPRI's TFP and PFP measures for developing countries for three-sub-periods between 1991 and 2014(1991-2000,2001-2010 and 2010-2014). These TFP and PFP estimates were generated using the most recent data from Economic Research Service of the United States Department of Agriculture (ERS-USDA), the FAOSTAT database of the Food and Agriculture Organization of the United Nations (FAO), and national statistical sources.

United States Total Factor Productivity (TFP): Manufacturing data was reported at 95.517 2009=100 in 2016. This records a decrease from the previous number of 98.642 2009=100 for 2015. United States Total Factor Productivity (TFP): Manufacturing data is updated yearly, averaging 91.097 2009=100 from Dec 1987 (Median) to 2016, with 30 observations. The data reached an all-time high of 103.798 2009=100 in 2010 and a record low of 77.682 2009=100 in 1992. United States Total Factor Productivity (TFP): Manufacturing data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G070: Total Factor Productivity.

Total Factor Productivity at Constant National Prices for United States was 1.01680 Index 2011=1 in January of 2019, according to the United States Federal Reserve. Historically, Total Factor Productivity at Constant National Prices for United States reached a record high of 1.01680 in January of 2019 and a record low of 0.56775 in January of 1950. Trading Economics provides the current actual value, an historical data chart and related indicators for Total Factor Productivity at Constant National Prices for United States - last updated from the United States Federal Reserve on March of 2025.

Graph and download economic data for Manufacturing Sector: Total Factor Productivity (MPU9900013) from 1988 to 2023 about productivity, sector, manufacturing, rate, and USA.

The employment growth in large firm with 100 or more employees was approximately 0.07 percent in 2019. Countries in conflict and in transition showed smaller growth than the rest in the Middle East and North Africa (MENA) region.

TFP: Non-Equipment Business Output (Consumption) data was reported at 0.227 % in Dec 2024. This records an increase from the previous number of -0.734 % for Sep 2024. TFP: Non-Equipment Business Output (Consumption) data is updated quarterly, averaging 0.466 % from Jun 1947 (Median) to Dec 2024, with 311 observations. The data reached an all-time high of 17.260 % in Mar 1950 and a record low of -10.197 % in Jun 2020. TFP: Non-Equipment Business Output (Consumption) data remains active status in CEIC and is reported by Federal Reserve Bank of San Francisco. The data is categorized under Global Database’s United States – Table US.G106: Total Factor Productivity.

United States TFP: Pvt Buss: Contribution of Capital Intensity data was reported at 100.119 2009=100 in 2017. This records an increase from the previous number of 99.865 2009=100 for 2016. United States TFP: Pvt Buss: Contribution of Capital Intensity data is updated yearly, averaging 92.358 2009=100 from Dec 1987 (Median) to 2017, with 31 observations. The data reached an all-time high of 100.119 2009=100 in 2017 and a record low of 78.949 2009=100 in 1987. United States TFP: Pvt Buss: Contribution of Capital Intensity data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G069: Total Factor Productivity.

The World Bank’s Prospects Group has constructed a comprehensive international database of potential growth. The database covers up to 173 countries for 1981-2021, and includes nine measures of potential growth of which the following eight are published:

• Multivariate filter (MVF)
• Hodrick-Prescott filter (HP)
• Christiano-Fitzgerald filter (CF)
• Baxter-King filter (BK)
• Butterworth filter (BW)
• Unobserved Components Model (UCM)
• 5-year ahead expectations (based on IMF’s WEO database vintages)
• Production function approach together with its decomposition: capital, labor and total factor productivity (TFP)

Kilic Celik, Kose, Ohnsorge, and Ruch (2023) provide detailed information on the database, document the steady decline in global potential growth over the past decade, and show the impact of adverse shock on potential growth.

The employment growth in Morocco in 2019 was approximately 0.1 percent. Countries in conflict and in transition showed smaller growth than the rest in the Middle East and North Africa (MENA) region.

Employment elasticity in the hotel and restaurant sector was the highest in Morocco in 2019 at about 2.33 points. Countries in conflict and in transition showed smaller employment growth than the rest in the Middle East and North Africa (MENA) region.

United States Total Factor Productivity: Non-Farm Private Business data was reported at 106.835 2009=100 in 2017. This records an increase from the previous number of 105.922 2009=100 for 2016. United States Total Factor Productivity: Non-Farm Private Business data is updated yearly, averaging 94.842 2009=100 from Dec 1987 (Median) to 2017, with 31 observations. The data reached an all-time high of 106.835 2009=100 in 2017 and a record low of 83.710 2009=100 in 1987. United States Total Factor Productivity: Non-Farm Private Business data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G070: Total Factor Productivity.

In 2020, almost 26 percent of the employment in the low income countries of the Middle East and North Africa (MENA) region were women. Countries in conflict and in transition had smaller employment growth than the rest in the Middle East and North Africa (MENA) region.

Total factor productivity (TFP) is the ratio of total output (crop and livestock products) to total production inputs (land, labor, capital and materials). An increase in TFP implies that more output is being produced from a constant amount of resources used in the production process. In the long run, TFP is the main driver of growth in agriculture and can be affected by policies and investment. Partial factor productivity (PFP) measures, such as labor and land productivity, are often used to measure agricultural prodcution performance because they are easy to estimate. These measures of productivity normally show higher rates of growth than TFP because growth in land and labor productivity could result from more intensive use of inputs, including fertilizer and machinery, rather than TFP increase. If productivity increases without the addition of more inputs, then the only source of growth is TFP. The data file provides estimates of IFPRI's TFP and PFP measures for developing countries for three-sub-periods between 1990 and 2011(1991-2000,2001-2007 and 2008-2013). These TFP and PFP estimates were generated using data from the Food and Agriculture Organization of the United Nations (FAO) on outputs and inputs. The output values are the FAO-constructed gross agricultural outputs, measured in constant 2004-2006 US dollars and smoothed using the Hodrick-Prescott filter. Each output v alue is a composite of 190 crop and livestock commodities aggregated using a constant set of global average prices from 2004-2006. Inputs include agricultural land, measured by the sum, in hectares, of cropland and permanent pasture; labor, measured by the number of animals in cattle equivalents; machinery, measured by the total amount of horsepower available from four-wheel tractors, pedestrian-operated tractors, and combine-threshers in use; and fertilizer, measured by tons of fertilizer nutrients used. The dataset of outputs and inputs was checked and cleaned using different statistical techniques. TFP estimates were obtained using Data Envelopment Analysis (DEA) techniques. These techniques have been extensively used because they make TFPs easy to compute, do not involve restrictive assumptions regarding economic behavior, such as cost minimization or profit maximization. On the other hand, DEA productivity estimates are sensitive to data noise and outliers and can suffer from the probel of ""unusual"" weights that are higher or lower than expected when aggregating inputs to meas ure TFP. Given these limitations, outlier detection methods were used to determine influential observations in the dataset and input weights were allowed to vary only within a certain range of expected values because specific lower and upper bounds were imposed for each input in different regions. Results are also afected by data characteristics and quality issues. In particular, the data series on fertilizer and machinery show high volatility and could result in high variablity of TFP estimates for some countries.