Mogadishu in Somalia led the ranking of cities with the highest population density in 2023, with ****** residents per square kilometer. When it comes to countries, Monaco is the most densely populated state worldwide.

Monaco led the ranking for countries with the highest population density in 2024, with nearly 26,000 residents per square kilometer. The Special Administrative Region of Macao came in second, followed by Singapore. The world’s second smallest country Monaco is the world’s second-smallest country, with an area of about two square kilometers and a population of only around 40,000. It is a constitutional monarchy located by the Mediterranean Sea, and while Monaco is not part of the European Union, it does participate in some EU policies. The country is perhaps most famous for the Monte Carlo casino and for hosting the Monaco Grand Prix, the world's most prestigious Formula One race. The global population Globally, the population density per square kilometer is about 60 inhabitants, and Asia is the most densely populated region in the world. The global population is increasing rapidly, so population density is only expected to increase. In 1950, for example, the global population stood at about 2.54 billion people, and it reached over eight billion during 2023.

As of July 2023, Monaco is the country with the highest population density worldwide, with an estimated population of nearly ****** per square kilometer.

Australia Population Density: People per Square Km data was reported at 3.382 Person/sq km in 2022. This records an increase from the previous number of 3.339 Person/sq km for 2021. Australia Population Density: People per Square Km data is updated yearly, averaging 2.263 Person/sq km from Dec 1961 (Median) to 2022, with 62 observations. The data reached an all-time high of 3.382 Person/sq km in 2022 and a record low of 1.365 Person/sq km in 1961. Australia Population Density: People per Square Km data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Australia – Table AU.World Bank.WDI: Population and Urbanization Statistics. Population density is midyear population divided by land area in square kilometers. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship--except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.;Food and Agriculture Organization and World Bank population estimates.;Weighted average;

In 2023, Washington, D.C. had the highest population density in the United States, with 11,130.69 people per square mile. As a whole, there were about 94.83 residents per square mile in the U.S., and Alaska was the state with the lowest population density, with 1.29 residents per square mile. The problem of population density Simply put, population density is the population of a country divided by the area of the country. While this can be an interesting measure of how many people live in a country and how large the country is, it does not account for the degree of urbanization, or the share of people who live in urban centers. For example, Russia is the largest country in the world and has a comparatively low population, so its population density is very low. However, much of the country is uninhabited, so cities in Russia are much more densely populated than the rest of the country. Urbanization in the United States While the United States is not very densely populated compared to other countries, its population density has increased significantly over the past few decades. The degree of urbanization has also increased, and well over half of the population lives in urban centers.

All cities with a population > 1000 or seats of adm div (ca 80.000)Sources and ContributionsSources : GeoNames is aggregating over hundred different data sources. Ambassadors : GeoNames Ambassadors help in many countries. Wiki : A wiki allows to view the data and quickly fix error and add missing places. Donations and Sponsoring : Costs for running GeoNames are covered by donations and sponsoring.Enrichment:add country name

Population of Urban Agglomerations with 300,000 Inhabitants or more in 2014, by city, 1950-2030 (thousands). Data for 1,692 cities contained in the Excel file.

Note: Each country has its own definition of what is 'urban' and therefore use exercise caution when comparing cities in different countries.

Data available from the United Nations, Department of Economic and Social Affairs, Population Division (2014). World Urbanization Prospects: The 2014 Revision, CD-ROM Edition.

Further detail of population estimates, land area, and population density for world urban areas with over 500,000 people (924 areas) is available with Demographia's World Urban Areas report (2014). Much of this data is based on the UN urban agglomerations, though a range of other sources are also used.

The majority of the Canadian population, about 60% is concentrated within a thin belt of land representing 2.2% of the land between Windsor, Ontario and Quebec City. Even though Canada is the second largest country in the world in terms of land area, it only ranks 33rd in terms of population. The agricultural areas in the Prairies and eastern Canada have higher population densities than the sparsely populated North, but not as high as southern Ontario or southern Quebec.

Data Usage Notice

This version is not recommended for download. Please check the newest version.

We would like to inform you that the updated GlobPOP dataset (2021-2022) have been available in version 2.0. The GlobPOP dataset (2021-2022) in the current version is not recommended for your work. The GlobPOP dataset (1990-2020) in the current version is the same as version 1.0.

Thank you for your continued support of the GlobPOP.

If you encounter any issues, please contact us via email at lulingliu@mail.bnu.edu.cn.

Introduction

Continuously monitoring global population spatial dynamics is essential for implementing effective policies related to sustainable development, such as epidemiology, urban planning, and global inequality.

Here, we present GlobPOP, a new continuous global gridded population product with a high-precision spatial resolution of 30 arcseconds from 1990 to 2020. Our data-fusion framework is based on cluster analysis and statistical learning approaches, which intends to fuse the existing five products(Global Human Settlements Layer Population (GHS-POP), Global Rural Urban Mapping Project (GRUMP), Gridded Population of the World Version 4 (GPWv4), LandScan Population datasets and WorldPop datasets to a new continuous global gridded population (GlobPOP). The spatial validation results demonstrate that the GlobPOP dataset is highly accurate. To validate the temporal accuracy of GlobPOP at the country level, we have developed an interactive web application, accessible at https://globpop.shinyapps.io/GlobPOP/, where data users can explore the country-level population time-series curves of interest and compare them with census data.

With the availability of GlobPOP dataset in both population count and population density formats, researchers and policymakers can leverage our dataset to conduct time-series analysis of population and explore the spatial patterns of population development at various scales, ranging from national to city level.

Data description

The product is produced in 30 arc-seconds resolution(approximately 1km in equator) and is made available in GeoTIFF format. There are two population formats, one is the 'Count'(Population count per grid) and another is the 'Density'(Population count per square kilometer each grid)

Each GeoTIFF filename has 5 fields that are separated by an underscore "_". A filename extension follows these fields. The fields are described below with the example filename:

GlobPOP_Count_30arc_1990_I32

Field 1: GlobPOP(Global gridded population)
Field 2: Pixel unit is population "Count" or population "Density"
Field 3: Spatial resolution is 30 arc seconds
Field 4: Year "1990"
Field 5: Data type is I32(Int 32) or F32(Float32)

More information

Please refer to the paper for detailed information:

Liu, L., Cao, X., Li, S. et al. A 31-year (1990–2020) global gridded population dataset generated by cluster analysis and statistical learning. Sci Data 11, 124 (2024). https://doi.org/10.1038/s41597-024-02913-0.

The fully reproducible codes are publicly available at GitHub: https://github.com/lulingliu/GlobPOP.

In 2022, the estimated population density of China was around 150.42 people per square kilometer. That year, China's population size declined for the first time in decades. Although China is the most populous country in the world, its overall population density is not much higher than the average population density in Asia. Uneven population distribution China is one of the largest countries in terms of land area, and its population density figures vary dramatically from region to region. Overall, the coastal regions in the East and Southeast have the highest population densities, as they belong to the more economically developed regions of the country. These coastal regions also have a higher urbanization rate. On the contrary, the regions in the West are covered with mountain landscapes which are not suitable for the development of big cities. Populous cities in China Several Chinese cities rank among the most populous cities in the world. According to estimates, Beijing and Shanghai will rank among the top ten megacities in the world by 2030. Both cities are also the largest Chinese cities in terms of land area. The previous colonial regions, Macao and Hong Kong, are two of the most densely populated cities in the world.

Disclaimer: These data are updated by the author and are not an official product of the Federal Reserve Bank of Cleveland.This project provides two sets of migration estimates for the major US metro areas. The first series measures net migration of people to and from the urban neighborhoods of the metro areas. The second series covers all neighborhoods but breaks down net migration to other regions by four region types: (1) high-cost metros, (2) affordable, large metros, (3) midsized metros, and (4) small metros and rural areas. These series were introduced in a Cleveland Fed District Data Brief entitled “Urban and Regional Migration Estimates: Will Your City Recover from the Pandemic?"The migration estimates in this project are created with data from the Federal Reserve Bank of New York/Equifax Consumer Credit Panel (CCP). The CCP is a 5 percent random sample of the credit histories maintained by Equifax. The CCP reports the census block of residence for over 10 million individuals each quarter. Each month, Equifax receives individuals’ addresses, along with reports of debt balances and payments, from creditors (mortgage lenders, credit card issuers, student loan servicers, etc.). An algorithm maintained by Equifax considers all of the addresses reported for an individual and identifies the individual’s most likely current address. Equifax anonymizes the data before they are added to the CCP, removing names, addresses, and Social Security numbers (SSNs). In lieu of mailing addresses, the census block of the address is added to the CCP. Equifax creates a unique, anonymous identifier to enable researchers to build individuals’ panels. The panel nature of the data allows us to observe when someone has migrated and is living in a census block different from the one they lived in at the end of the preceding quarter. For more details about the CCP and its use in measuring migration, see Lee and Van der Klaauw (2010) and DeWaard, Johnson and Whitaker (2019). DefinitionsMetropolitan areaThe metropolitan areas in these data are combined statistical areas. This is the most aggregate definition of metro areas, and it combines Washington DC with Baltimore, San Jose with San Francisco, Akron with Cleveland, etc. Metro areas are combinations of counties that are tightly linked by worker commutes and other economic activity. All counties outside of metropolitan areas are tracked as parts of a rural commuting zone (CZ). CZs are also groups of counties linked by commuting, but CZ definitions cover all counties, both metropolitan and non-metropolitan. High-cost metropolitan areasHigh-cost metro areas are those where the median list price for a house was more than $200 per square foot on average between April 2017 and April 2022. These areas include San Francisco-San Jose, New York, San Diego, Los Angeles, Seattle, Boston, Miami, Sacramento, Denver, Salt Lake City, Portland, and Washington-Baltimore. Other Types of RegionsMetro areas with populations above 2 million and house price averages below $200 per square foot are categorized as affordable, large metros. Metro areas with populations between 500,000 and 2 million are categorized as mid-sized metros, regardless of house prices. All remaining counties are in the small metro and rural category.To obtain a metro area's total net migration, sum the four net migration values for the the four types of regions.Urban neighborhoodCensus tracts are designated as urban if they have a population density above 7,000 people per square mile. High density neighborhoods can support walkable retail districts and high-frequency public transportation. They are more likely to have the “street life” that people associate with living in an urban rather than a suburban area. The threshold of 7,000 people per square mile was selected because it was the average density in the largest US cities in the 1930 census. Before World War II, workplaces, shopping, schools and parks had to be accessible on foot. Tracts are also designated as urban if more than half of their housing units were built before WWII and they have a population density above 2,000 people per square mile. The lower population density threshold for the pre-war neighborhoods recognizes that many urban tracts have lost population since the 1960s. While the street grids usually remain, the area also needs su

United Kingdom UK: Population Density: People per Square Km data was reported at 272.898 Person/sq km in 2017. This records an increase from the previous number of 271.134 Person/sq km for 2016. United Kingdom UK: Population Density: People per Square Km data is updated yearly, averaging 235.922 Person/sq km from Dec 1961 (Median) to 2017, with 57 observations. The data reached an all-time high of 272.898 Person/sq km in 2017 and a record low of 218.245 Person/sq km in 1961. United Kingdom UK: Population Density: People per Square Km data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United Kingdom – Table UK.World Bank.WDI: Population and Urbanization Statistics. Population density is midyear population divided by land area in square kilometers. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship--except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.; ; Food and Agriculture Organization and World Bank population estimates.; Weighted average;

The majority of the Canadian population, about 60% is concentrated within a thin belt of land representing 2.2% of the land between Windsor, Ontario and Quebec City. Even though Canada is the second largest country in the world in terms of land area, it only ranks 33rd in terms of population. The agricultural areas in the Prairies and eastern Canada have higher population densities than the sparsely populated North, but not as high as southern Ontario or southern Quebec.

• The current US Census Bureau world population estimate in June 2019 shows that the current global population is 7,577,130,400 people on Earth, which far exceeds the world population of 7.2 billion in 2015. Our estimate based on UN data shows the world's population surpassing 7.7 billion.
• China is the most populous country in the world with a population exceeding 1.4 billion. It is one of just two countries with a population of more than 1 billion, with India being the second. As of 2018, India has a population of over 1.355 billion people, and its population growth is expected to continue through at least 2050. By the year 2030, India is expected to become the most populous country in the world. This is because India’s population will grow, while China is projected to see a loss in population.
• The following 11 countries that are the most populous in the world each have populations exceeding 100 million. These include the United States, Indonesia, Brazil, Pakistan, Nigeria, Bangladesh, Russia, Mexico, Japan, Ethiopia, and the Philippines. Of these nations, all are expected to continue to grow except Russia and Japan, which will see their populations drop by 2030 before falling again significantly by 2050.
• Many other nations have populations of at least one million, while there are also countries that have just thousands. The smallest population in the world can be found in Vatican City, where only 801 people reside.
• In 2018, the world’s population growth rate was 1.12%. Every five years since the 1970s, the population growth rate has continued to fall. The world’s population is expected to continue to grow larger but at a much slower pace. By 2030, the population will exceed 8 billion. In 2040, this number will grow to more than 9 billion. In 2055, the number will rise to over 10 billion, and another billion people won’t be added until near the end of the century. The current annual population growth estimates from the United Nations are in the millions - estimating that over 80 million new lives are added yearly.
• This population growth will be significantly impacted by nine specific countries which are situated to contribute to the population growth more quickly than other nations. These nations include the Democratic Republic of the Congo, Ethiopia, India, Indonesia, Nigeria, Pakistan, Uganda, the United Republic of Tanzania, and the United States of America. Particularly of interest, India is on track to overtake China's position as the most populous country by 2030. Additionally, multiple nations within Africa are expected to double their populations before fertility rates begin to slow entirely.

Content

• In this Dataset, we have Historical Population data for every Country/Territory in the world by different parameters like Area Size of the Country/Territory, Name of the Continent, Name of the Capital, Density, Population Growth Rate, Ranking based on Population, World Population Percentage, etc. >Dataset Glossary (Column-Wise):
• Rank: Rank by Population.
• CCA3: 3 Digit Country/Territories Code.
• Country/Territories: Name of the Country/Territories.
• Capital: Name of the Capital.
• Continent: Name of the Continent.
• 2022 Population: Population of the Country/Territories in the year 2022.
• 2020 Population: Population of the Country/Territories in the year 2020.
• 2015 Population: Population of the Country/Territories in the year 2015.
• 2010 Population: Population of the Country/Territories in the year 2010.
• 2000 Population: Population of the Country/Territories in the year 2000.
• 1990 Population: Population of the Country/Territories in the year 1990.
• 1980 Population: Population of the Country/Territories in the year 1980.
• 1970 Population: Population of the Country/Territories in the year 1970.
• Area (km²): Area size of the Country/Territories in square kilometers.
• Density (per km²): Population Density per square kilometer.
• Growth Rate: Population Growth Rate by Country/Territories.
• World Population Percentage: The population percentage by each Country/Territories.

The statistic shows the 30 largest countries in the world by area. Russia is the largest country by far, with a total area of about 17 million square kilometers.

Population of Russia

Despite its large area, Russia - nowadays the largest country in the world - has a relatively small total population. However, its population is still rather large in numbers in comparison to those of other countries. In mid-2014, it was ranked ninth on a list of countries with the largest population, a ranking led by China with a population of over 1.37 billion people. In 2015, the estimated total population of Russia amounted to around 146 million people. The aforementioned low population density in Russia is a result of its vast landmass; in 2014, there were only around 8.78 inhabitants per square kilometer living in the country. Most of the Russian population lives in the nation’s capital and largest city, Moscow: In 2015, over 12 million people lived in the metropolis.

Green spaces in urban areas-- like remnant habitat, parks, constructed wetlands, and street trees-- supply multiple benefits. Many studies show green spaces in and near urban areas play important roles harboring biodiversity and promoting human well-being. On the other hand, evidence suggests that greater human population density enables compact, low-carbon cities that spare habitat conversion at the fringes of expanding urban areas, while also allowing more walkable and livable cities. How then can urban areas have abundant green spaces as well as density?

This data archive contains data created as part of a scientific manuscript that attempts to answer this question, entitled "Denser and greener cities: Green interventions to achieve both urban density and nature". Please see that manuscript for details on sources of data and details of methodology.

We found that there is a negative correlation between population density and urban green spaces. For Functional Urban Areas in the OECD, a doubling of density is associated with a 2.9% decline in tree cover. We argue that there are competing tradeoffs between the benefits of density for sustainability and the benefits of nature for human well-being. Planners must decide an appropriate density by choosing where to be on this tradeoff curve, taking into account city-specific urban planning goals and context. However, while the negative correlation between population density and tree cover is modest at the level of US urbanized areas (R²=0.22), it is weak at the US Census block level (R²=0.05), showing that there are significant brightspots, neighborhoods that manage to have more tree canopy than would be expected based upon their level of density. We then describe techniques for how urban planners and designers can create more brightspots, identifying a typology of urban forms and listing green interventions appropriate for each form. We also analyze policies that enable these green interventions illustrating them with the case studies of Curitiba and Singapore. We conclude that while there are tensions between density and urban green spaces, an urban world that is both green and dense is possible, if society chooses to take advantage of the available green interventions and create it.

20 year Projected Urban Growth scenarios. Base year is 2000. Projected year in this dataset is 2020.

By 2020, most forecasters agree, California will be home to between 43 and 46 million residents-up from 35 million today. Beyond 2020 the size of California's population is less certain. Depending on the composition of the population, and future fertility and migration rates, California's 2050 population could be as little as 50 million or as much as 70 million. One hundred years from now, if present trends continue, California could conceivably have as many as 90 million residents.

Where these future residents will live and work is unclear. For most of the 20th Century, two-thirds of Californians have lived south of the Tehachapi Mountains and west of the San Jacinto Mountains-in that part of the state commonly referred to as Southern California. Yet most of coastal Southern California is already highly urbanized, and there is relatively little vacant land available for new development. More recently, slow-growth policies in Northern California and declining developable land supplies in Southern California are squeezing ever more of the state's population growth into the San Joaquin Valley.

How future Californians will occupy the landscape is also unclear. Over the last fifty years, the state's population has grown increasingly urban. Today, nearly 95 percent of Californians live in metropolitan areas, mostly at densities less than ten persons per acre. Recent growth patterns have strongly favored locations near freeways, most of which where built in the 1950s and 1960s. With few new freeways on the planning horizon, how will California's future growth organize itself in space? By national standards, California's large urban areas are already reasonably dense, and economic theory suggests that densities should increase further as California's urban regions continue to grow. In practice, densities have been rising in some urban counties, but falling in others.

These are important issues as California plans its long-term future. Will California have enough land of the appropriate types and in the right locations to accommodate its projected population growth? Will future population growth consume ever-greater amounts of irreplaceable resource lands and habitat? Will jobs continue decentralizing, pushing out the boundaries of metropolitan areas? Will development densities be sufficient to support mass transit, or will future Californians be stuck in perpetual gridlock? Will urban and resort and recreational growth in the Sierra Nevada and Trinity Mountain regions lead to the over-fragmentation of precious natural habitat? How much water will be needed by California's future industries, farms, and residents, and where will that water be stored? Where should future highway, transit, and high-speed rail facilities and rights-of-way be located? Most of all, how much will all this growth cost, both economically, and in terms of changes in California's quality of life?

Clearly, the more precise our current understanding of how and where California is likely to grow, the sooner and more inexpensively appropriate lands can be acquired for purposes of conservation, recreation, and future facility siting. Similarly, the more clearly future urbanization patterns can be anticipated, the greater our collective ability to undertake sound city, metropolitan, rural, and bioregional planning.

Consider two scenarios for the year 2100. In the first, California's population would grow to 80 million persons and would occupy the landscape at an average density of eight persons per acre, the current statewide urban average. Under this scenario, and assuming that 10% percent of California's future population growth would occur through infill-that is, on existing urban land-California's expanding urban population would consume an additional 5.06 million acres of currently undeveloped land. As an alternative, assume the share of infill development were increased to 30%, and that new population were accommodated at a density of about 12 persons per acre-which is the current average density of the City of Los Angeles. Under this second scenario, California's urban population would consume an additional 2.6 million acres of currently undeveloped land. While both scenarios accommodate the same amount of population growth and generate large increments of additional urban development-indeed, some might say even the second scenario allows far too much growth and development-the second scenario is far kinder to California's unique natural landscape.

This report presents the results of a series of baseline population and urban growth projections for California's 38 urban counties through the year 2100. Presented in map and table form, these projections are based on extrapolations of current population trends and recent urban development trends. The next section, titled Approach, outlines the methodology and data used to develop the various projections. The following section, Baseline Scenario, reviews the projections themselves. A final section, entitled Baseline Impacts, quantitatively assesses the impacts of the baseline projections on wetland, hillside, farmland and habitat loss.

In 2023, the population density in South Korea stood at around *** inhabitants per square kilometer, slightly up from *** in the previous year. The nationwide population density has been increasing steadily over the past decades. The highest density was in Seoul, the capital of South Korea, with ****** people per square kilometer. UrbanizationSouth Korea was primarily an agricultural nation. In the decades following its independence from Japanese rule in 1945, both the dictatorships and democratic governments that governed South Korea focused on industrialization and modernization of the country. The urban population has grown by about **** million over the past 20 years, while the rural population has fallen by around *** million. In 2023, around ** percent of the population lived in an urban area. The most populous city SeoulSeoul’s high population density is not surprising. The capital city is typically grouped with the province of Gyeonggi, which resembles a donut with Seoul at its center, and the metropolitan port city of Incheon, collectively known as the Seoul Capital Area. This is one of the largest metropolitan areas in the world and serves as the political, economic, and cultural center of South Korea. With more than **** millio* residents, half of South Korea’s population lives in this area.

Innovation and night light intensity for cities in developing countries.

Social and economic figures for 67 large West German cities. The data aggregated at city level have been collected for most topics over several years, but not necessarily over the entire reference time period.

Topics: 1. Situation of the city: surface area of the city; fringe location in the Federal Republic.

1. Residential population: total residential population; German and foreign residential population.

2. Population movement:live births; deaths; influx; departures; birth rate; death rate; population shifts; divorce rate; migration rate; illegitimate births.

3. Education figures: school degrees; occupational degrees; university degrees.

4. Wage and income: number of taxpayers in the various tax classes as well as municipality income tax revenue in the respective classes; calculated income figures, such as e.g. inequality of income distribution, mean income or mean wage of employees as well as standard deviation of these figures; GINI index.

5. Gross domestic product and gross product: gross product altogether; gross product organized according to area of business; gross domestic product; employees in the economic sectors.

6. Taxes and debts: debt per resident; income tax and business tax to which the municipality is entitled; municipality tax potential and indicators for municipality economic strength.

7. Debt repayment and management expenditures: debt repayment, interest expenditures, management expenditures and personnel expenditures.

8. From the ´BUNTE´ City Test of 1979 based on 100 respondents per city averages of satisfaction were calculated. satisfaction with: central location of the city, the number of green areas, historical buildings, the number of high-rises, the variety of the citizens, openness to the world, the dialect spoken, the sociability, the density of the traffic network, the OEPNV prices {local public passenger transport}, the supply of public transportation, provision with culture, the selection for consumers, the climate, clean air, noise pollution, the leisure selection, real estate prices, the supply of residences, one´s own payment, the job market selection, the distance from work, the number of one´s friends, contact opportunities, receptiveness of the neighbors, local recreational areas, sport opportunities and the selection of further education possibilities.

9. Traffic and economy: airport and Intercity connection; number of kilometers of subway available, kilometers of streetcar, and kilometers of bus lines per resident; car rate; index of traffic quality; commuters; property prices; prices for one´s own home; purchasing power.

10. Crime: recorded total crime and classification according to armed robbery, theft from living-rooms, of automobiles as well as from motor vehicles, robberies and purse snatching; classification according to young or adult suspects with these crimes; crime stress figures. 12. Welfare: welfare recipients and social expenditures; proportion of welfare recipients in the total population and classification according to German and foreign recipients; aid with livelihood; expenditures according to the youth welfare law; kindergarten openings; culture expenditures per resident. 13. Foreigners: proportion of foreigners in the residential population.

11. Students: number of German students and total number of students; proportion of students in the residential population.

12. Unemployed: unemployment rate; unemployed according to employment office districts and employment office departments.

13. Places of work: workers employed in companies, organized according to area of business.

14. Government employees: full-time, part-time and total government employees of federal government, states and municipalities as well as differentiated according to workers, employees, civil servants and judges.

15. Employees covered by social security according to education and branch of economy: proportion of various education levels in the individual branches of the economy.