This statistic shows the labor productivity per person employed and hour worked in relation to the average gross domestic product (GDP) of the European Union (EU-28) in Germany from 2005 to 2016. Labor productivity compared to the EU average remained above average throughout the measured time period and reached a peak in 2005 at 108.5.

Germany - Real labour productivity per person employed was -0.30 % year-on-year in March of 2025, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Germany - Real labour productivity per person employed - last updated from the EUROSTAT on July of 2025. Historically, Germany - Real labour productivity per person employed reached a record high of 11.60 % year-on-year in June of 2021 and a record low of -9.90 % year-on-year in June of 2020.

DE: Multifactor Productivity: Capital Stock Output Ratio: % Point Contribution to Labour Productivity Growth data was reported at 0.620 % in 2022. This records a decrease from the previous number of 1.116 % for 2021. DE: Multifactor Productivity: Capital Stock Output Ratio: % Point Contribution to Labour Productivity Growth data is updated yearly, averaging 1.209 % from Dec 1985 (Median) to 2022, with 38 observations. The data reached an all-time high of 3.739 % in 1990 and a record low of -5.549 % in 2009. DE: Multifactor Productivity: Capital Stock Output Ratio: % Point Contribution to Labour Productivity Growth data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Germany – Table DE.OECD.PDB: Multifactor and Capital Productivity: OECD Member: Annual.

Productivity in Germany increased to 95 points in May from 93.60 points in April of 2025. This dataset provides the latest reported value for - Germany Productivity - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Germany DE: Capital Quality: Capital Stock Output Ratio: % Point Contribution to Labour Productivity Growth data was reported at 0.256 % in 2022. This records an increase from the previous number of 0.245 % for 2021. Germany DE: Capital Quality: Capital Stock Output Ratio: % Point Contribution to Labour Productivity Growth data is updated yearly, averaging 0.308 % from Dec 1985 (Median) to 2022, with 38 observations. The data reached an all-time high of 0.585 % in 2000 and a record low of 0.182 % in 1994. Germany DE: Capital Quality: Capital Stock Output Ratio: % Point Contribution to Labour Productivity Growth data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Germany – Table DE.OECD.PDB: Investment in Capital Stocks and Services: OECD Member: Annual.

Description:From an economic point of view the production encompasses manufacturing, including related ‘industrial services’ as long as they are provided in the production industry. After the guidelines of the official statistics on the measurement of production, all products produced to be sold including repair works, montages and contract processing should be captured. Own consumption and wage work is included. For the calculation of the production indices the primary used data are the monthly production surveys. For this surveys reports of chosen local units of enterprises in the production, in the mining sector and extraction of stones and earth with 50 or more employees are used. Until 2006 the reporting threshold was fixed for 20 or more employees. The manufacturing trade is always included. The production index should demonstrate the development of the quantitative production of the production industry and its sub-areas in Germany, adjusted for chances in prices and structures to provide continuous data. Differences in size and changes in structures can be avoided, by presenting the production output not in total numbers, but in from of index number series orientated towards a basis year. For the calculation of production index numbers, current monthly production values (quantity of sales or sale values) are presented as a ratio of the monthly averages of the base year. Until 1993 the Federal Statistical Office calculated two types of production indices: gross-production indices and net-production indices. From the index system 1991=100 on there is only one production index, defined as e net production index. Both index types differ from one another among other things by the definition of the performance dimensions (value added or value of gross production) and by the way it is structured (net production index by economic sectors, gross production index by types of commodities). Indices of net production in the Federal Republic of Germany exist since 1950. During the past decades the base year changed several times and also the content wise classification economic sectors changed repeatedly trough the introduction of new classification systems. The series with different base years overlap, which gives the opportunity to calculate a continuous series with one single base, if the classification of economic sectors did not change in the entire period. Content-related interlinking of indices with different bases is controversial and the results can only be interpreted with care and under certain assumptions. The net production indices are also used to measure productivity in the production industry. Labor productivity (of a local unit, an enterprise, an economic sector or of the entire national economy) can be defined as the ratio of quantity of production and labor input in a certain period. Interpreting this coefficient, it is important to note that labor productivity also depends on the use of other production factors. The index for labor productivity is defined as the “production results per input component of the working volume”. Two different manifestations of the working volume are used for the calculation of the index: (1) hours of work by employees and (2) number of hours worked. Until 1994 in addition a distinction between “number of workers” and “number of employees” was made. The total national working productivity serves as an indicator for economic performance and competitiveness of an economic sector or of the entire national economy with regard to the entire labor input. Labor productivity (after the results of the national accounts) is apparently the most used productivity notion for the entire economy. It shows how effective the input labor is used in the production process. Anyway, it is important to note that the partial productivity indicator not only depends on the factor work but also on the endowment of a certain sector or the entire economy with machines and their degree of modernity and on the infrastructure, which also has an impact on the production result.Productivity can be measured regarding the following two aspects: production result per worker (per capita productivity) and production result per working hour (hourly productivity). For the entire national economy the labor productivity is measured as the ratio of the gross national product (in constant prices) and the average number of employees. To look at the development of labor productivity of an entire national economy, usually the real gross domestic product is used. When comparing economic sectors within a country, the added values of the economic sectors can be used in the respective prices with regard to one employee or one hour of work. Data tables in HISTAT:A. Index for the industrial net production A.01 Index for the industrial net production by industry groups, monthly data (1950-1994)A.02 Production index for the production industry (1991-2014) B. Index for the industrial gross production B.01 Index for t...

The study deals with the reconstruction of German secular economic trends associated with a data-compilation of historical time series concerning the economic development.

Index of tables in HISTAT (On-line Database ´Historical Statistics´):

• Population Development in Germany (1200-2002)
• Emigration from Germany (1820-2002)
• Live Birth and deceased per 1000 Inhabitants in Germany (1820-2000)
• Life expectancy of men and women in Germany (1871- 2001)
• Expansion rate of real GDP per capita of the population
• Real GDP per capita of population in Germany (1850-2002)
• Expansion rate of real GDP per capita of population in Germany (1851-2002)
• Hectare-output of wheat and rye in Germany (1850-2000)
• Gross-Value-Added of Primary Sector in comparison to the entire national economy (1850-2002)
• Percental share of Gross-Value-Added of Primary Sector in the entire Gross-Value-Added of national economy (1850 -2002)
• Price index of living costs and actual earnings in England (1264-1953)
• Employees in Germany (1800-2003)
• Average hours of work on a weekly basis in mining, industry and handcraft (1850-2002)
• Overall fulfilled hours of work in Germany (1850-2003)
• GDP per Capita, volume of work and average hours of work per week(1850-2002)
• Index of real wages in Germany (1810-2002)
• Unemployment rate in Germany (1887-2002)
• Percentage of employees in primary, secondary and tertiary sector of total employment (1800-2003)
• Capital stock in Germany (1850-2000)
• Netinvestment in Germany (1850-2002)
• Netinvestment rate in Germany (1850-2003)
• Index of capital intensity and of labour productivity (GDP per capita) in Germany (1850-2001)
• Return on capital in Germany (1850-1998)
• Capital ratio in Germany (1850-2000)
• Total Factorproductivity in Germany (1870-1999)
• Education rates in Germany and in USA (1870-1992)
• Number of grants in Germany (1812-2003) and in USA (1791-2000)

Abstract copyright UK Data Service and data collection copyright owner. The primary aim of the research project was to present an overview of Britain's relative competitive performance in the postwar period. Previous research in this area has concentrated on either the total economy or on manufacturing. The aim of the project was to broaden the scope of research by examining competitive performance for all sectors of the aggregate economy. To do so, a dataset was constructed to enable measurement of productivity (both labour and total factor productivity) and unit labour costs comparing Britain to four of her major competitors, i.e. the US, France, Germany and Japan. The research was concerned with to what extent the performance at the aggregate economy level was affected by the inclusion of non-market services (health, education and government), which are poorly measured in the national accounts. Differences in performance between service sectors and production industries were also analysed. Main Topics: The dataset contains the raw data necessary to enable an evaluation of Britain's relative competitive performance at the sector level. Hence the dataset contains annual time series, from 1950 to 1995, on real output (generally value added), number of persons engaged, average annual hours worked, net capital stocks, labour force skills and labour's share of value added. It also includes benchmark estimates of relative productivity levels for 1993. The data are available for a maximum of 33 sectors, some of which are broad sectors and some comprise sub-industries with these broad sectors. The sectors included are : 1. Agriculture, forestry and fishing; 2. Mining and oil refining (2.1 oil and gas extraction, 2.2 other mining, 2.3 mineral oil refining); 3. Utilities (3.1 electricity, 3.2 gas, 3.3 water supply); 4. Manufacturing 5. Construction 6. Distributive trades (6.1 wholesale trade, 6.2 retail trade, 6.3 hotels and catering); 7. Transport and communications (7.1 rail transport, 7.2 water transport, 7.3 air transport, 7.4 other transport & transport services, 7.5 communications); 8. Financial & business services (8.1 banking & finance, 8.2 insurance, 8.3 business services); 9. Miscellaneous personal services; 10. Non-market services (10.1 health, 10.2 education, 10.3 government) plus the total for the aggregate economy and the total over market sectors (excluding non-market sectors). The manufacturing sectors are : 4.1. Chemicals and allied products (4.11 chemicals, 4.12 rubber and plastics); 4.2. Metals (4.21 basic metals and 4.22 metal products); 4.3. Engineering industries (4.31 mechanical engineering, 4.32 office machinery, 4.33 electrical engineering, 4.34 mo tor vehicles, 4.45 other transport equipment, 4.36 instrument engineering); 4.4. Textile and related products (4.41 textiles, 4.42 clothing, footwear and leather); 4.5. Food, drink and tobacco and 4.6. Other manufacturing (4.61 non-metallic mineral products, 4.62 wood & furniture, 4.63 paper & printing, 4.64 miscellaneous manufacturing. The data originate from official publications but include adjustment to render them internationally comparable. Data limitations imply that the series are not always available for all sectors in all countries. The most complete data series are for the US, the UK and Germany - less detail is available for France and Japan. The data represent in some cases a complete, and in some cases a partial transcription of original sources. Adjustments were made to the original sources to render them consistent across both time and countries. For example, in constructing real output for the US, the data are those published for Construction, indexed to 1993=100. For the communications sector, however, the US industry definition includes telecommunications, radio and TV, whereas communications in all other countries comprise telecommunications and postal services. Hence for the US output of the postal services (included with the Federal Government) was estimated and added to output in telecommunications. For further details, please see documentation. The dataset contains the following files : NISECQ.xls: Real value added by sector, (index, 1993=100). NISECMQ.xls: Real value added in manufacturing industries, (index, 1993=100). NISECE.xls: Number of persons engaged by sector, (thousands of persons). NISECME.xls: Number of persons engaged in manufacturing, (thousands of persons). NISECHR.xls: Annual average hours per worker by sector, (number of hours). NISECMHR.xls: Annual average hours per worker in manufacturing, (number of hours). NISECPR.xls: Value added per hour worked by sector, (index, 1993=100). NISECMPR.xls: Value added per hour worked in manufacturing, (index, 1993=100). NISECK.xls: Capital services by sector, (index, 1993=100). NISECMK.xls: Capital services in manufacturing, (index, 1993=100). (this file does include a spreadsheet for Japan ) NISECLS.xls: Labour's share of value added by sector, (proportions). NISECMLS.xls: Labour's share of value added in manufacturing, (proportions). (this file does include a spreadsheet for Japan) NISECSK.xls: Labour force skills by sector, divided into higher level, intermediate level and low skills (percent of the workforce). Note: these data are available only for the US, the UK and Germany. NISECMSK.xls: Labour force skills in manufacturing, divided into higher level, intermediate level and low skills (percent of the workforce). Note: these data are available only for the US, the UK and Germany. NISECLV.xls: Relative levels of value added per hour worked and capital per hour worked in 1993, (UK=100). This contains one spreadsheet for sectors and one for manufacturing. No information recorded

Keywords; Search terms: historical time series; historical statistics; histat / HISTAT .

Abstract:

Quantitative analysis of growth trends and economic cycles of the German economy in the phase of early and high industrialization based on indicators in the form of longer time series.

Topics:

a) Proof of relevant different growth patterns within the national economy, determination of number and average length of the cycles of individual indicators as well as dating of the prevailing economic movement, insight into the connections between individual economic sectors;

b) creation of indicator time series for population, bankruptcies, agriculture, grocery business, cotton industry, mining, iron and steel industry, monetary and credit business.

Time Series (1820-1913) in the downloadsystem HISTAT:

• Germanys mean population;

• Birthrate, Marriage Rate, Death Rate;

• Insolvencies in the German Empire;

• Annual Average Bank Rate, Hamburg / Berlin (in %);

• Note Balance Sheets of German Financial Institutions and Banks at the End of the Year (in Mio. Mark);

• Crop Net Production of german Agriculture in Constant Prices of 1913 (in Mio. Mark);

• Wholsale Prices of Vegetable Food in the German Empire, Index, 1913=100, Constant Currency (in %);

• Consumption of Shugar (in 1000t);

• Wholsale Prices of Industrial Basic Matirials in the German Empire, Index, 1913=100, Constant Currency (in %.);

• Output of Prussian Black Coal Mining Förderungsmenge des preußischen Steinkohlebergbaus (in Mio. t );

• Chief Board of Mines district (Oberbergamtsbezirk) Dortmunts Labour Productivity of Black Coal Mining (in t/Mann);

• Hot Metal Production (in 1000t);

• Import Prices of shottisch Pig-Iron, Hamburg (in Mark/t);

• Gross-Investment of Germanys Cotton-Mills (in 1000 Mark);

• Spinning Margin of German Cotton-Mills (in Pfennig/kg);

• Yarn Production of German Cotton-Mills (in 1000t );

Germany DE: GDP: 2015 Price: USD: Gross Value Added Per Worker: Agriculture, Forestry, and Fishing data was reported at 0.057 USD mn in 2023. This records an increase from the previous number of 0.055 USD mn for 2022. Germany DE: GDP: 2015 Price: USD: Gross Value Added Per Worker: Agriculture, Forestry, and Fishing data is updated yearly, averaging 0.037 USD mn from Dec 1991 (Median) to 2023, with 33 observations. The data reached an all-time high of 0.057 USD mn in 2023 and a record low of 0.019 USD mn in 1994. Germany DE: GDP: 2015 Price: USD: Gross Value Added Per Worker: Agriculture, Forestry, and Fishing data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Gross Domestic Product: Real. Value added per worker is a measure of labor productivity—value added per unit of input. Value added denotes the net output of a sector after adding up all outputs and subtracting intermediate inputs. Data are in constant 2015 U.S. dollars. Agriculture corresponds to the International Standard Industrial Classification (ISIC) tabulation categories A and B (revision 3) or tabulation category A (revision 4), and includes forestry, hunting, and fishing as well as cultivation of crops and livestock production.;Derived using World Bank national accounts data and OECD National Accounts data files, and employment data from International Labour Organization, ILOSTAT database.;Weighted average;

Germany DE: Agriculture Value Added per Worker: 2010 Price data was reported at 41,992.961 USD in 2016. This records an increase from the previous number of 40,221.633 USD for 2015. Germany DE: Agriculture Value Added per Worker: 2010 Price data is updated yearly, averaging 25,326.241 USD from Dec 1991 (Median) to 2016, with 26 observations. The data reached an all-time high of 42,328.069 USD in 2009 and a record low of 15,927.567 USD in 1994. Germany DE: Agriculture Value Added per Worker: 2010 Price data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Agricultural Production and Consumption. Agriculture value added per worker is a measure of agricultural productivity. Value added in agriculture measures the output of the agricultural sector (ISIC divisions 1-5) less the value of intermediate inputs. Agriculture comprises value added from forestry, hunting, and fishing as well as cultivation of crops and livestock production. Data are in constant 2010 U.S. dollars.; ; Derived from World Bank national accounts files and Food and Agriculture Organization, Production Yearbook and data files.; Weighted average;