Germany Multidimensional Poverty Headcount Ratio: World Bank: % of total population data was reported at 0.300 % in 2020. This stayed constant from the previous number of 0.300 % for 2019. Germany Multidimensional Poverty Headcount Ratio: World Bank: % of total population data is updated yearly, averaging 0.200 % from Dec 2010 (Median) to 2020, with 10 observations. The data reached an all-time high of 0.300 % in 2020 and a record low of 0.100 % in 2015. Germany Multidimensional Poverty Headcount Ratio: World Bank: % of total population 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: Social: Poverty and Inequality. The multidimensional poverty headcount ratio (World Bank) is the percentage of a population living in poverty according to the World Bank's Multidimensional Poverty Measure. The Multidimensional Poverty Measure includes three dimensions – monetary poverty, education, and basic infrastructure services – to capture a more complete picture of poverty.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

The Gross Domestic Product (GDP) in Germany was worth 4659.93 billion US dollars in 2024, according to official data from the World Bank. The GDP value of Germany represents 4.39 percent of the world economy. This dataset provides the latest reported value for - Germany GDP - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Graph and download economic data for Bank Deposits to GDP for Germany (DDOI02DEA156NWDB) from 1970 to 2021 about Germany, deposits, banks, depository institutions, and GDP.

Germany DE: GDP: Growth: Household Final Consumption Expenditure per Capita data was reported at -1.528 % in 2023. This records a decrease from the previous number of 3.171 % for 2022. Germany DE: GDP: Growth: Household Final Consumption Expenditure per Capita data is updated yearly, averaging 1.355 % from Dec 1971 (Median) to 2023, with 53 observations. The data reached an all-time high of 5.289 % in 1971 and a record low of -5.930 % in 2020. Germany DE: GDP: Growth: Household Final Consumption Expenditure per Capita 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: Annual Growth Rate. Annual percentage growth of household final consumption expenditure per capita, which is calculated using household final consumption expenditure in constant 2010 prices and World Bank population estimates. Household final consumption expenditure (private consumption) is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments and fees to governments to obtain permits and licenses. Here, household consumption expenditure includes the expenditures of nonprofit institutions serving households, even when reported separately by the country.;World Bank national accounts data, and OECD National Accounts data files.;Weighted average;

Gross domestic savings (% of GDP) in Germany was reported at 24.9 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Germany - Gross domestic savings (% of GDP) - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

Abstract

This research, designed by the World Bank, and supported by the Department for International Development (DFID), aims to highlight the unprecedented transformation of the urban systems in the ECA region in the last decades, and to look at this shifts from the demographic, economic, and spatial prospectives.

Cities in ECA database comprises data from 5,549 cities in 15 countries of the Eastern Europe and Central Asia region, as defined by the World Bank Group, and from the United Kingdom and Germany. Database information for each city is in three dimensions: demographic, spatial, and economic.

The starting point to construct the Cities in ECA database was to obtain from each of the countries the list of official cities and these cities' population data. Population data collected for cities falls on or around three years: 1989, 1999, and 2010 (or the latest year available). The official list of "cities" was geo-referenced and overlaid with globally-available spatial data to produce city-level indicators capturing spatial characteristics (e.g., urban footprint) and proxies for economic activity. City-level spatial characteristics, including urban footprints (or extents) for the years 1996, 2000, and 2010 and their temporal evolution, were obtained from the Global Nighttime Lights (NTL) dataset. City-level proxies for economic activity were also estimated based on the NTL dataset. Nighttime Lights (NLS) data is produced by the Defense Meteorological Satellite Program (DMSP) - Optical Line Scanner (OLS) database and maintained by the National Oceanic and Atmospheric Administration (NOAA).

Geographic coverage

Albania, Belarus, Bulgaria, Georgia, Germany, Kazakhstan, Kyrgyz Republic, Moldova, Poland, Romania, Russian Federation, Serbia, Tajikistan, Turkey, Ukraine, United Kingdom, Uzbekistan

Analysis unit

• a city

Kind of data

Process-produced data [pro]

Mode of data collection

Other [oth]

Graph and download economic data for Bank's Cost to Income Ratio for Germany (DDEI07DEA156NWDB) from 2000 to 2021 about ratio, Germany, expenditures, income, banks, and depository institutions.

Germany DE: GDP: Real: per Capita data was reported at 39,960.579 EUR in 2023. This records an increase from the previous number of 39,819.663 EUR for 2022. Germany DE: GDP: Real: per Capita data is updated yearly, averaging 27,920.436 EUR from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 39,960.579 EUR in 2023 and a record low of 11,356.630 EUR in 1960. Germany DE: GDP: Real: per Capita 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. GDP per capita is gross domestic product divided by midyear population. GDP at purchaser's prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in constant local currency.;World Bank national accounts data, and OECD National Accounts data files.;;

Central bank assets to GDP (%) in Germany was reported at 22.23 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Germany - Central bank assets to GDP - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

Birth rate, crude (per 1,000 people) in Germany was reported at 8.3 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Germany - Birth rate, crude - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

Germany DE: GDP: Growth data was reported at -0.305 % in 2023. This records a decrease from the previous number of 1.806 % for 2022. Germany DE: GDP: Growth data is updated yearly, averaging 2.230 % from Dec 1961 (Median) to 2023, with 63 observations. The data reached an all-time high of 7.418 % in 1969 and a record low of -5.694 % in 2009. Germany DE: GDP: Growth 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: Annual Growth Rate. Annual percentage growth rate of GDP at market prices based on constant local currency. Aggregates are based on constant 2015 prices, expressed in U.S. dollars. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources.;World Bank national accounts data, and OECD National Accounts data files.;Weighted average;

Abstract

Sustainable Development Goal (SDG) target 2.1 commits countries to end hunger, ensure access by all people to safe, nutritious and sufficient food all year around. Indicator 2.1.2, “Prevalence of moderate or severe food insecurity based on the Food Insecurity Experience Scale (FIES)”, provides internationally-comparable estimates of the proportion of the population facing difficulties in accessing food. More detailed background information is available at http://www.fao.org/in-action/voices-of-the-hungry/fies/en/ .

The FIES-based indicators are compiled using the FIES survey module, containing 8 questions. Two indicators can be computed: 1. The proportion of the population experiencing moderate or severe food insecurity (SDG indicator 2.1.2), 2. The proportion of the population experiencing severe food insecurity.

These data were collected by FAO through the Gallup World Poll. General information on the methodology can be found here: https://www.gallup.com/178667/gallup-world-poll-work.aspx. National institutions can also collect FIES data by including the FIES survey module in nationally representative surveys.

Microdata can be used to calculate the indicator 2.1.2 at national level. Instructions for computing this indicator are described in the methodological document available under the "DOCUMENTATION" tab above. Disaggregating results at sub-national level is not encouraged because estimates will suffer from substantial sampling and measurement error.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

Individuals of 15 years or older with access to landline and/or mobile phones.

Kind of data

Sample survey data [ssd]

Sampling procedure

A dual frame (landline and mobile phone frames) was used to complete 1,000 telephone surveys. About 50% of the completes were from the mobile phone sample whereas landline completes accounted for the remaining 50%. Exclusions: NA Design effect: 2.4

Mode of data collection

Computer Assisted Telephone Interview [cati]

Cleaning operations

Statistical validation assesses the quality of the FIES data collected by testing their consistency with the assumptions of the Rasch model. This analysis involves the interpretation of several statistics that reveal 1) items that do not perform well in a given context, 2) cases with highly erratic response patterns, 3) pairs of items that may be redundant, and 4) the proportion of total variance in the population that is accounted for by the measurement model.

Sampling error estimates

The margin of error is estimated as 4.8. This is calculated around a proportion at the 95% confidence level. The maximum margin of error was calculated assuming a reported percentage of 50% and takes into account the design effect.

Graph and download economic data for Percentage of Foreign Banks Among Total Banks for Germany (DDOI13DEA156NWDB) from 1995 to 2013 about foreign, Germany, percent, banks, and depository institutions.

Liabilities to BIS banks, locational, total in Germany was reported at 2244138325000 in 2025, according to the World Bank collection of development indicators, compiled from officially recognized sources. Germany - Liabilities to BIS banks, locational, total - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

Bank capital to total assets (%) in Germany was reported at 5.93 % in 2020, according to the World Bank collection of development indicators, compiled from officially recognized sources. Germany - Bank capital to total assets - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

Loans from nonresident banks (amounts outstanding) to GDP (%) in Germany was reported at 45.21 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Germany - Loans from nonresident banks (amounts outstanding) to GDP - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

Urban population growth (annual %) in Germany was reported at --0.30005 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Germany - Urban population growth (annual %) - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.

By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

Germany DE: Tariff Rate: Applied: Simple Mean: Manufactured Products data was reported at 1.440 % in 2022. This records a decrease from the previous number of 1.670 % for 2021. Germany DE: Tariff Rate: Applied: Simple Mean: Manufactured Products data is updated yearly, averaging 1.750 % from Dec 2000 (Median) to 2022, with 23 observations. The data reached an all-time high of 3.040 % in 2001 and a record low of 1.440 % in 2022. Germany DE: Tariff Rate: Applied: Simple Mean: Manufactured Products 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: Trade Tariffs. Simple mean applied tariff is the unweighted average of effectively applied rates for all products subject to tariffs calculated for all traded goods. Data are classified using the Harmonized System of trade at the six- or eight-digit level. Tariff line data were matched to Standard International Trade Classification (SITC) revision 3 codes to define commodity groups. Effectively applied tariff rates at the six- and eight-digit product level are averaged for products in each commodity group. When the effectively applied rate is unavailable, the most favored nation rate is used instead. To the extent possible, specific rates have been converted to their ad valorem equivalent rates and have been included in the calculation of simple mean tariffs. Manufactured products are commodities classified in SITC revision 3 sections 5-8 excluding division 68.;World Bank staff estimates using the World Integrated Trade Solution system, based on data from United Nations Conference on Trade and Development's Trade Analysis and Information System (TRAINS) database.;;The tariff data for the European Union (EU) apply to EU Member States in alignment with the EU membership for the respective countries/economies and years. In the context of the tariff data, the EU membership for a given country/economy and year is defined for the entire year during which the country/economy was a member of the EU (irrespective of the date of accession to or withdrawal from the EU within a given year). The tariff data for the EU are, thus, applicable to Belgium, France, Germany, Italy, Luxembourg, and the Netherlands (EU Member State(s) since 1958), Denmark and Ireland (EU Member State(s) since 1973), the United Kingdom (EU Member State(s) from 1973 until 2020), Greece (EU Member State(s) since 1981), Spain and Portugal (EU Member State(s) since 1986), Austria, Finland, and Sweden (EU Member State(s) since 1995), Czech Republic, Estonia, Cyprus, Latvia, Lithuania, Hungary, Malta, Poland, Slovakia, and Slovenia (EU Member State(s) since 2004), Romania and Bulgaria (EU Member State(s) since 2007), Croatia (EU Member State(s) since 2013). For more information, please revisit the technical note on bilateral applied tariff (https://wits.worldbank.org/Bilateral-Tariff-Technical-Note.html).

Abstract

Tajikistan Jobs, Skills, and Migration Survey 2013 is one of three identical household surveys conducted in Central Asia in 2013 by the World Bank in collaboration with German Federal Enterprise for International Cooperation (GIZ). Kyrgyz Republic and Uzbekistan were the other countries.

The purpose of the survey was to collect data on employment, migration, cognitive and non-cognitive skills as well as consumption. Conducted from July to September 2013, the survey collected comprehensive information not typically captured by traditional household surveys. It included two distinct instruments: a core questionnaire and a skills questionnaire.

The core questionnaire covered such topics as education, employment, migration, health expenditure, remittances, government transfers, financial services, subjective poverty, housing conditions, and household expenditures. The skills questionnaire contained detailed modules on labor and work expectations, migration and preparation for migration, language skills, and technical skill training. The non-cognitive test modules of the skills questionnaire were based on World Bank Skills Toward Employment and Productivity (STEP) surveys.

The sample size of the core questionnaire was 6,300 households with a total of 35,770 individuals. Given that either one or two individuals per household were randomly selected to participate in the skills questionnaire, this sample consisted of 7,929 individuals.

Geographic coverage

National coverage

Analysis unit

Households and individuals.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample size of the core questionnaire is 6,300 households with a total of 35,770 individuals. Given that either one or two individual per household was randomly selected to partake in the skills questionnaire, this sample consists of 7,929 individuals.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires were first designed in English and then translated into Russian and Tajik.