Keywords; Search terms: historical time series; historical statistics; histat / HISTAT . Abstract: The author’s aim is to give an overview of the development of the official German statistics and specially the official employment-statistics in the former German Democratic Republic (GDR). Data-Sources of the official statistics of the GDR about the occupation has been:- four occupation censes, which has been carried out together with the population census (1950, 1964, 1971, 1981);- special surveys about the occupation carried out by the statistical service of the former GDR;- workplace-statistics and sector-specific reporting including information about employees, done by the SZS;- further statistical reporting by governmental organisations about employment. In order to realise comparability between the official statistics of the former GDR with the official statistics of the Federal Republic of Germany (FRG), the Federal Statistical Office made substantial conversions and formed new statistical groups respectively (see special tables dealing with backward projection of the GDR-statistics, Table-Part D. and E.). Topics: Subcategorisation of the Study (Tables of the ZA-Database HISTAT):Some Data of the GDR-employment-statistics: I. The official employment statistics of the GDR:
A. Employed persons and population B. Employees and apprentices by occupational status C. Employees by economic sectors II. Making the former GDR’s labour force statistics comparable with the labour force statistics of the former Federal Republic of Germany (FRG) D. Federal Statistical Office, Wiesbaden: Some Information of backward projection of the GDR’s labour force statistics into FRG-classification („ Systematics of economic sectors“, Issue 1979 (WZ)“) III. Selected Information of population and occupation census (1950, 1964, 1971, 1981), according to the systematics of the Federal Statistics. E. Federal Statistical Office, Wiesbaden: Employees of the former GDR by population and occupation census (conversion 1964, 1971, 1981) according to („ Systematics of economic sectors“, Issue 1979 (WZ)“)

Germany FSO Forecast: Number of Households: 2 Persons data was reported at 15,413.000 Number th in 2035. This records a decrease from the previous number of 15,415.000 Number th for 2034. Germany FSO Forecast: Number of Households: 2 Persons data is updated yearly, averaging 15,199.000 Number th from Dec 2017 (Median) to 2035, with 19 observations. The data reached an all-time high of 15,417.000 Number th in 2033 and a record low of 14,274.000 Number th in 2017. Germany FSO Forecast: Number of Households: 2 Persons data remains active status in CEIC and is reported by Federal Statistics Office Germany. The data is categorized under Global Database’s Germany – Table DE.H023: Number of Households: Forecast: Federal Statistics Office Germany.

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Since 2005, the Diagnosis Related Groups (DRG) statistics have provided annual information on morbidity events and morbidity trends in inpatient care, as well as on the volume and structure of demand for services, over and above the existing official hospital statistics. In particular, type of illness, case-flat-rate hospital statistic (DRGs), operations and procedures as well as length of stay and department are collected.

The aggregated data are freely accessible.

Germany FSO Projection: Population: Berlin data was reported at 3,929.000 Person th in 2060. This records a decrease from the previous number of 3,930.000 Person th for 2059. Germany FSO Projection: Population: Berlin data is updated yearly, averaging 3,875.000 Person th from Dec 2014 (Median) to 2060, with 47 observations. The data reached an all-time high of 3,931.000 Person th in 2057 and a record low of 3,471.000 Person th in 2014. Germany FSO Projection: Population: Berlin data remains active status in CEIC and is reported by Federal Statistics Office Germany. The data is categorized under Global Database’s Germany – Table DE.G002: Population: Projection: Federal Statistics Office Germany.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Household

UNITS IDENTIFIED: - Dwellings: Yes - Vacant units: Yes - Households: Yes - Individuals: Yes - Group quarters: Yes - Special populations: No

UNIT DESCRIPTIONS: - Dwellings: Living quarters which could be in residential buildings and non-residential buildings - Households: A household is a group of persons who live and keep house together. A person living alone forms a household. Subtenants are treated as separate households. - Group quarters: Institutions were collective dwelling for the accommodation and care of citizens who for reasons of working, training or studying, or for educational, health, social or other reasons needed to be accommodated collectively.

Universe

Total population entitled to reside in households

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Federal Statistical Office

SAMPLE DESIGN: 25% sample of households drawn based on anonymization methodology by the Federal Statistical Office.

SAMPLE UNIT: Household

SAMPLE FRACTION: 25%

SAMPLE SIZE (person records): 4,110,749

Mode of data collection

Face-to-face [f2f]

Research instrument

There are 4 forms: (1) household questionnaire containing questions for all persons in the household; (2) dwelling questionnaire containing questions for all dwellings; (3) building questionnaire containing questions for all residential buildings; and (4) institution questionnaire.

Response rate

COVERAGE: 100%

The German inflation rate has returned to normal levels of around 2.2 percent, based on preliminary figures for 2024. Compared to skyrocketing rates in 2022 and 2023, this can be seen as an improvement of the national economic situation. Various factors influenced the recent development of inflation in Germany. These are the same that pushed inflation levels around the rest of the world, particularly since the beginning of the Russia-Ukraine war in 2022. The most recent recorded annual inflation rate in Germany is within the normal range defined by central banks internationally, which is generally between 1.5 and four percent a year. The 2.2 percent for 2024 are not only noticeably lower than the preceding two years, but also less than in 2021, one of the COVID-19 pandemic lockdown years in Germany. 2022 and 2023 followed on the heels of the challenges posed by the pandemic which were already straining the national economy: supply chain interruptions and delays, transport problems, labor shortages across sectors and industries. These issues continue to partially impact the economy today.

Germany FSO Projection: Population: High Birth Rate Based Trend data was reported at 71,236.000 Person th in 2060. This records a decrease from the previous number of 71,533.000 Person th for 2059. Germany FSO Projection: Population: High Birth Rate Based Trend data is updated yearly, averaging 78,472.000 Person th from Dec 2014 (Median) to 2060, with 47 observations. The data reached an all-time high of 81,691.000 Person th in 2019 and a record low of 71,236.000 Person th in 2060. Germany FSO Projection: Population: High Birth Rate Based Trend data remains active status in CEIC and is reported by Federal Statistics Office Germany. The data is categorized under Global Database’s Germany – Table DE.G003: Population: Projection: Federal Statistics Office Germany.

Data-Compilation. Overview of the development of population and its structure in Germany (Federal Republic of Germany) from 1947 to 1999 on the basis of the German Federal Statistical Office data.

Topics (HISTAT):

A. Population and Population development; B. Population Movement; C. Private Households; D. Families; E. Women in the age of 15 and older: Family status, number of children.

This dataset features three gridded population dadasets of Germany on a 10m grid. The units are people per grid cell.

Datasets

DE_POP_VOLADJ16: This dataset was produced by disaggregating national census counts to 10m grid cells based on a weighted dasymetric mapping approach. A building density, building height and building type dataset were used as underlying covariates, with an adjusted volume for multi-family residential buildings.

DE_POP_TDBP: This dataset is considered a best product, based on a dasymetric mapping approach that disaggregated municipal census counts to 10m grid cells using the same three underyling covariate layers.

DE_POP_BU: This dataset is based on a bottom-up gridded population estimate. A building density, building height and building type layer were used to compute a living floor area dataset in a 10m grid. Using federal statistics on the average living floor are per capita, this bottom-up estimate was created.

Please refer to the related publication for details.

Temporal extent

The building density layer is based on Sentinel-2 time series data from 2018 and Sentinel-1 time series data from 2017 (doi: http://doi.org/10.1594/PANGAEA.920894)

The building height layer is representative for ca. 2015 (doi: 10.5281/zenodo.4066295)

The building types layer is based on Sentinel-2 time series data from 2018 and Sentinel-1 time series data from 2017 (doi: 10.5281/zenodo.4601219)

The underlying census data is from 2018.

Data format

The data come in tiles of 30x30km (see shapefile). The projection is EPSG:3035. The images are compressed GeoTiff files (.tif). There is a mosaic in GDAL Virtual format (.vrt), which can readily be opened in most Geographic Information Systems.

Further information

For further information, please see the publication or contact Franz Schug (franz.schug@geo.hu-berlin.de). A web-visualization of this dataset is available here.

Publication

Schug, F., Frantz, D., van der Linden, S., & Hostert, P. (2021). Gridded population mapping for Germany based on building density, height and type from Earth Observation data using census disaggregation and bottom-up estimates. PLOS ONE. DOI: 10.1371/journal.pone.0249044

Acknowledgements

Census data were provided by the German Federal Statistical Offices.

Funding This dataset was produced with funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950).

CCSS Research Support collaborates with the Institute for Employment Research (IAB) of the German Federal Employment Agency enabling approved researchers to securely access confidential administrative microdata on labor markets. Currently available data are listed here: https://fdz.iab.de/en/FDZ_Overview_of_Data.aspx These resources are available to any researcher approved by IAB, no affiliation with Cornell is required.

Access is available in person at the IAB Research Data Center at CCSS-RS. See https://fdz.iab.de/en/FDZ_Data_Access.aspx for details on data access.

The data files contain detailed information on employment, unemployment benefit receipts, participation in labor market programs and registered job search, and a large number of socio-economic characteristics.

The most restrictive data may be accessed in person at the IAB Research Data Center located in the CCSS-RS offices. Access to confidential administrative microdata is provided through a thin client connection directly to the IAB servers in Germany. In addition to Cornell University, other locations in the U.S. where this access is possible include: University of Michigan; University of California at Berkeley; Harvard University; University of California Los Angeles; and Princeton University.

Access to the IAB’s less restrictive confidential microdata, referred to as Scientific Use Files (SUF), are available. These files are similar in origin to the highly restrictive files but have been factually anonymized enabling wider access. IAB will check for each specific case if and under what conditions a SUF file can be stored and accessed from a personal workplace. For this, potential users will have to complete a data security concept, as described here: https://fdz.iab.de/en/FDZ_Data_Access/FDZ_Scientific_Use_Files.aspx.

Germany FSO Projection: Population: Younger Population Based Trend data was reported at 76,931.000 Person th in 2060. This records a decrease from the previous number of 77,089.000 Person th for 2059. Germany FSO Projection: Population: Younger Population Based Trend data is updated yearly, averaging 81,067.000 Person th from Dec 2014 (Median) to 2060, with 47 observations. The data reached an all-time high of 82,178.000 Person th in 2022 and a record low of 76,931.000 Person th in 2060. Germany FSO Projection: Population: Younger Population Based Trend data remains active status in CEIC and is reported by Federal Statistics Office Germany. The data is categorized under Global Database’s Germany – Table DE.G003: Population: Projection: Federal Statistics Office Germany.

Germany FSO Projection: Population: Sachsen data was reported at 3,239.000 Person th in 2060. This records a decrease from the previous number of 3,257.000 Person th for 2059. Germany FSO Projection: Population: Sachsen data is updated yearly, averaging 3,689.000 Person th from Dec 2014 (Median) to 2060, with 47 observations. The data reached an all-time high of 4,044.000 Person th in 2014 and a record low of 3,239.000 Person th in 2060. Germany FSO Projection: Population: Sachsen data remains active status in CEIC and is reported by Federal Statistics Office Germany. The data is categorized under Global Database’s Germany – Table DE.G003: Population: Projection: Federal Statistics Office Germany.

Graph and download economic data for Percent of Employment in Manufacturing in Germany (DISCONTINUED) (DEUPEFANA) from 1970 to 2012 about Germany, percent, manufacturing, and employment.

In February 2025, based on preliminary figures, consumer prices in Germany increased by 2.3 percent compared to the same month of the previous year. The inflation rate is calculated using the price increase of a product basket defined by the German Federal Statistical Office. This product basket contains services and products, on which the average consumer spends money throughout the year. This includes expenses for groceries, clothes, rent, power, telecommunications, recreational activities and raw materials (i.e. gas, oil), as well as federal fees and taxes.The term inflation means the devaluation of money caused by the increase of the price level of products (consumer goods, investment goods). The Consumer Price Index shows the price trends for private consumption expenses and shows the current inflation level when increasing.

The estimated number of people working in offices in Germany rose annually between 2010 and 2022, except for a slight dip in 2020. The German Federal Employment Agency does not report on the number of employees working in offices, which means that no data is available that covers the exact figure. The estimation is based on the development of employment in the key economic sectors with primarily clerical work. In 2022, the number of office workers in Germany was estimated at 10.3 million. That is not an exact number and should be treated as a rough estimate, as the sectors excluded from the calculation also feature a certain, though low, ratio of office-based jobs. Secondly, the sectors included are also not 100 percent office-based.

Graph and download economic data for Real Gross Domestic Product for Germany (CLVMNACNSAB1GQDE) from Q1 1991 to Q4 2024 about Germany, real, and GDP.

Public expenditures are an important tool of the government to carry out its tasks and to reach specified target values of state tasks. The State (= public sector) with its diverse economic activities is an important part of the economic process. It contributes not only directly but also indirectly and to a significant extent to the formation, distribution, and use of domestic product. Revenues and expenditures are the instruments of fiscal policy. This area of public finance is usually at the beginning of the analysis, because the task fulfillment is most expressed in practical functions of public spending. The political relevant question in the field of public expenditure is in this context, for which areas of government activities the financial resources are used. The functional structure of government spending may be indicative in a qualified sense of the political priorities. The functional classification of government expenditure by function is one of many ways to structure the diversity of public expenditure. The institutional structure shows to what extent the individual corporations contribute to the financing of total expenditure (with ‘individual corporations’ is meant regional corporations as: federal government, German Laender (or German States), local authorities, as well as social security, associations of communes, special funds of the federal government, and financial shares of the EU). In conjunction with the functional classification the institutional structure also shows what are the expenditure’s priorities and the main field of activity of the various public authorities and budgets. In terms of the public spending’s overall economic efficiency the most important criterion is the issue whether and how macro-economic resources are used. This criterion is reflected by the aggregate classification (national accounts) of expenditures into so called transfer expenditures: payments to the enterprises (grant-in-aid), payments to private households (especially social spending); so called real expenditures, which are staff expenditures and material expenditures; further expenditures (investment in physical capital, as purchase of land, credits, guarantees, acquisition of holdings). The government’s share of GDP derived from the sum of necessary expenditures needed for the fulfillment of the government’s tasks, as a function of historical, economical and political development of a country, expressed as public expenditure quota in form of the public expenditure share on the gross national product (GNP) at market prices, the GDP (gross domestic product).

This data compilation is based on the classifications outlined above for government expenditures. In addition to the characteristics of public expenditures and revenues major characteristics of the financial statistics are considered. Both the reports of the Federal Statistical Office (financial statistics) and the financial reports of the Federal Ministry of Finance are used. In addition, a summary of the public expenditure as calculated by the Bundesbank (according to information of the Federal Statistical Office) are gathered for comparison. When using different sources, a more detailed specification of the data is required: the definition of public expenditures used respectively by the different sources, has to be mentioned, especially regarding to the inclusion of social security, public service organizations and public companies.

Data tables in HISTAT:

A. Overviews:

A.01a Entwicklung der Ausgaben und Einnahmen der öffentlichen Haushalte nach Arten, in Mill. DM (1950–2000) A.01b Entwicklung der Ausgaben und Einnahmen der öffentlichen Haushalte nach Arten, in DM je Einwohner (1950–2000) A.02a Entwicklung der Ausgaben nach ausgewählten Aufgabenbereichen, in Mill. DM (1950 -2000) A.02b Entwicklung der Ausgaben nach ausgewählten Aufgabenbereichen, in DM je Einwohner (1950-2000) A.03 Öffentliche Ausgaben insgesamt nach zusammengefassten Aufgabenbereichen (1950-2000) A.04 Sozial- und Inlandsprodukt, öffentlicher Gesamthaushalt (bereinigte Einnahmen und Ausgaben), Quoten (1950-2000) A.05 Sozial- und Inlandsprodukt, öffentlicher Gesamthaushalt (Einnahmen und Ausgaben) - ohne Sozialversicherung (1962-2000) A.05 Sozial- und Inlandsprodukt, öffentlicher Gesamthaushalt (Einnahmen und Ausgaben) - ohne Sozialversicherung und Zweckverbände (1962-2000)

B. Development of the public budgets expenditures by groups of public corporations and by nature of expenditure

B.01 Bereinigte Ausgaben nach Berichtskreisen (1950-2000) B.02 Personalausgaben nach Berichtskreisen (1950-2000) B.03 Laufender Sachaufwand nach Berichtskreisen (1950-2000) B.04 Zinsausgaben am Kreditmarkt nach Berichtskreisen (1950-2000) B.05 Renten, Unterstützungen u. ä. nach Berichtskreisen (1950-2000) B.06 Baumaßnahmen nach Berichtskreisen (1950-2000)

C. Development of the public expenditures by groups of public corporations and area of responsibility

C.1 Summe aller...

Sources: Publications of the Federal Statistical Office, scientific publications

This is a compact excerpt of GDP data for Germany from the publication: Thomas Rahlf, Volkswirtschaftliche Gesamtrechnung, in: Thomas Rahlf (Ed.), Deutschland in Daten. Zeitreihen zur Historischen Statistik, 2nd ed., Bonn: Bundeszentrale für politische Bildung 2022, pp. 192-205.

According to current research, it is not possible to calculate a reliable gross national product, or gross domestic product for Germany for the 19th century. Instead of Hoffmann’s calculations, the net national product calculated by Pfister (2020) should be used.

For the first half of the 20th century, the calculations of Ritschl / Spoerer (1997) should still be chosen.

For the period from 1950 to 1970, the data in Spoerer / Ritschl (1997) are identical with the more comprehensive publication Federal Statistical Office (2021), which contains unrevised results before the introduction of the European System of Accounts in 1995.

For 1970 to 1990, the data published by Ritschl / Spoerer (1997) can be used if comparability of this period with the period before is more important than with the period after.

If a comparison with the period after is more important, for 1970 to 1990 the data from Federal Statistical Office (2021), should be used. These are recalculated after the 1991 and 2002 revisions, but not after the 2011, 2014, or 2018 revisions.

The data from 1991 onward fit the previous ones only to a limited extent because they have been recalculated based on the 2011, 2014, and 2018 revisions.

Pfister, Ulrich, The Crafts–Harley view of German industrialization: an independent estimate of the income side of net national product, 1851–1913, in: European Review of Economic History 24/3 (2020), S. 502‐521.

Ritschl, Albrecht/Spoerer, Mark, Das Bruttosozialprodukt Deutschlands nach den amtlichen Volkseinkommens‐ und Sozialproduktstatistiken 1901‐1995, in: Jahrbuch für Wirtschaftsgeschichte 1997, S. 27‐54.

Statistisches Bundesamt (Hrsg.): Bevölkerung und Wirtschaft 1872–1972, Stuttgart/Mainz 1972

Statistisches Bundesamt (Hrsg.) 2010, Volkswirtschaftliche Gesamtrechnungen. Ergebnisse in jeweiligenPreisen und in Preisen von 1991 nach ESVG, 2. Auflage, 1950 bis 1970, Wiesbaden (unveröffentlicht).

Statistisches Bundesamt (Hrsg.), Fachserie 18, Volkswirtschaftliche Gesamtrechnungen. Reihe 1.5: Inlandsproduktberechnung ‐ Lange Reihen ab 1970, Jg. 2020, Stuttgart.