About this dataset

Context

The dataset tabulates the population of New Germany by race. It includes the population of New Germany across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of New Germany across relevant racial categories.

Key observations

The percent distribution of New Germany population by race (across all racial categories recognized by the U.S. Census Bureau): 96.24% are white, 0.17% are Black or African American, 0.34% are Asian, 0.85% are some other race and 2.39% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the New Germany
• Population: The population of the racial category (excluding ethnicity) in the New Germany is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of New Germany total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for New Germany Population by Race & Ethnicity. You can refer the same here

In 2024, 40-59-year-olds made up the largest age group in Germany, at around 22.3 million people. The most recent figures confirm that the next-largest age group was 65 years and older, at roughly 19 million. Aging population With the number of people belonging to older age groups visibly outstripping younger ones, in recent years it has become clear that Germany’s population is aging. In fact, figures on age structure in Germany depict a constant trend of a slowly increasing population share aged over 65 since 2012. Meanwhile, the share of population members aged 0 to 14 years has been falling, which was also reflected in the fluctuating national birth rate in recent years. A look at the future Germany’s current total population is around 83.6 million. While this number is predicted to increase, the same goes for the age group of 65 years and older. This means that the national population will continue to age.

In 1800, the region of Germany was not a single, unified nation, but a collection of decentralized, independent states, bound together as part of the Holy Roman Empire. This empire was dissolved, however, in 1806, during the Revolutionary and Napoleonic eras in Europe, and the German Confederation was established in 1815. Napoleonic reforms led to the abolition of serfdom, extension of voting rights to property-owners, and an overall increase in living standards. The population grew throughout the remainder of the century, as improvements in sanitation and medicine (namely, mandatory vaccination policies) saw child mortality rates fall in later decades. As Germany industrialized and the economy grew, so too did the argument for nationhood; calls for pan-Germanism (the unification of all German-speaking lands) grew more popular among the lower classes in the mid-1800s, especially following the revolutions of 1948-49. In contrast, industrialization and poor harvests also saw high unemployment in rural regions, which led to waves of mass migration, particularly to the U.S.. In 1886, the Austro-Prussian War united northern Germany under a new Confederation, while the remaining German states (excluding Austria and Switzerland) joined following the Franco-Prussian War in 1871; this established the German Empire, under the Prussian leadership of Emperor Wilhelm I and Chancellor Otto von Bismarck. 1871 to 1945 - Unification to the Second World War The first decades of unification saw Germany rise to become one of Europe's strongest and most advanced nations, and challenge other world powers on an international scale, establishing colonies in Africa and the Pacific. These endeavors were cut short, however, when the Austro-Hungarian heir apparent was assassinated in Sarajevo; Germany promised a "blank check" of support for Austria's retaliation, who subsequently declared war on Serbia and set the First World War in motion. Viewed as the strongest of the Central Powers, Germany mobilized over 11 million men throughout the war, and its army fought in all theaters. As the war progressed, both the military and civilian populations grew increasingly weakened due to malnutrition, as Germany's resources became stretched. By the war's end in 1918, Germany suffered over 2 million civilian and military deaths due to conflict, and several hundred thousand more during the accompanying influenza pandemic. Mass displacement and the restructuring of Europe's borders through the Treaty of Versailles saw the population drop by several million more.

Reparations and economic mismanagement also financially crippled Germany and led to bitter indignation among many Germans in the interwar period; something that was exploited by Adolf Hitler on his rise to power. Reckless printing of money caused hyperinflation in 1923, when the currency became so worthless that basic items were priced at trillions of Marks; the introduction of the Rentenmark then stabilized the economy before the Great Depression of 1929 sent it back into dramatic decline. When Hitler became Chancellor of Germany in 1933, the Nazi government disregarded the Treaty of Versailles' restrictions and Germany rose once more to become an emerging superpower. Hitler's desire for territorial expansion into eastern Europe and the creation of an ethnically-homogenous German empire then led to the invasion of Poland in 1939, which is considered the beginning of the Second World War in Europe. Again, almost every aspect of German life contributed to the war effort, and more than 13 million men were mobilized. After six years of war, and over seven million German deaths, the Axis powers were defeated and Germany was divided into four zones administered by France, the Soviet Union, the UK, and the U.S.. Mass displacement, shifting borders, and the relocation of peoples based on ethnicity also greatly affected the population during this time. 1945 to 2020 - Partition and Reunification In the late 1940s, cold war tensions led to two distinct states emerging in Germany; the Soviet-controlled east became the communist German Democratic Republic (DDR), and the three western zones merged to form the democratic Federal Republic of Germany. Additionally, Berlin was split in a similar fashion, although its location deep inside DDR territory created series of problems and opportunities for the those on either side. Life quickly changed depending on which side of the border one lived. Within a decade, rapid economic recovery saw West Germany become western Europe's strongest economy and a key international player. In the east, living standards were much lower, although unemployment was almost non-existent; internationally, East Germany was the strongest economy in the Eastern Bloc (after the USSR), though it eventually fell behind the West by the 1970s. The restriction of movement between the two states also led to labor shortages in t...

About this dataset

Context

The dataset tabulates the Non-Hispanic population of New Germany by race. It includes the distribution of the Non-Hispanic population of New Germany across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of New Germany across relevant racial categories.

Key observations

Of the Non-Hispanic population in New Germany, the largest racial group is White alone with a population of 557 (98.24% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the New Germany
• Population: The population of the racial category (for Non-Hispanic) in the New Germany is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of New Germany total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for New Germany Population by Race & Ethnicity. You can refer the same here

In 2023, around 20 percent of the population with a migrant background had a secondary or elementary school education. 38.5 percent had some type of university degree.

In the immediate aftermath of the Second World War, Germany was split into four zones, each administered by France, the United Kingdom, the United States and the Soviet Union respectively. In 1949, the Soviet-controlled zone formed the German Democratic Republic (East Germany), while the rest became the Federal Republic of Germany (West Germany). In this time, Berlin was also split into four zones, and the three non-Soviet zones formed West Berlin, which was a part of West Germany (although the West's administrative capital was moved to Bonn). One population grows, while the other declines Between 1949 and 1961, an estimated 2.7 million people migrated from East to West Germany. East Germany had a communist government with a socialist economy and was a satellite state of the Soviet Union, whereas West Germany was a liberal democracy with a capitalist economy, and western autonomy increased over time. Because of this difference, West Germany was a much freer society with more economic opportunities. During the German partition, the population of the west grew, from 51 million in 1950 to 62.7 million in 1989, whereas the population of East Germany declined from 18.4 million to just 16.4 million during this time. Little change after reunification In 1989, after four decades of separation, the process of German reunification began. The legal and physical barriers that had split the country were removed, and Germans could freely travel within the entire country. Despite this development, population growth patterns did not change. The population of the 'new states' (East Germany) continued to decline, whereas the population of the west grew, particularly in the 1990s, the first decade after reunification. The reasons for this continued imbalance between German population in the east and west, is mostly due to a low birth rate and internal migration within Germany. Despite the fact that levels of income and unemployment in the new states have gotten closer to those reported for the west (a major obstacle after reunification), life and opportunities in the west continue to attract young Germans from rural areas in the east with detrimental effect on the economy and demography of the new states.

Several scholars have concluded that ethnic diversity has negative consequences for social trust. However, recent research has called into question whether ethnic diversity per se has detrimental effects, or whether lower levels of trust in diverse communities simply reflect a higher concentration of less trusting groups, such as poor people, minorities, or immigrants. Drawing upon a nationally representative sample of the German population (GSOEP), we make two contributions to this debate. First, we examine how ethnic diversity at the neighborhood level–specifically the proportion of immigrants in the neighborhood–is linked to social trust focusing on the compositional effect of poverty. Second, in contrast to the majority of current research on ethnic diversity, we use a behavioral measure of trust in combination with fine-grained (zip-code level) contextual measures of ethnic composition and poverty. Furthermore, we are also able to compare the behavioral measure to a standard attitudinal trust question. We find that household poverty partially accounts for lower levels of trust, and that after controlling for income, German and non-German respondents are equally trusting. However, being surrounded by neighbors with immigrant background is also associated with lower levels of social trust.

1941 marked an escalation of the Second World War in Europe. By the middle of the year, Germany and its European allies had already consolidated power across most of the continent, with only the United Kingdom and Soviet Union not under Axis control or on neutral terms with Germany. As population sizes were fundamental to the war effort, both in terms of military manpower and the workforce of the home front, the annexation of other countries proved vital in supplying new volunteers, conscripts, and forced laborers for the Axis war effort. Together, Germany and Austria had a similar population to the rest of Europe's Axis powers combined, with all giving a total population of 154 million. However, the total population of the Axis-occupied territories in Europe was comparable to the Axis home fronts themselves, at almost 130 million people

Germans in the East Eastern Europe had a sizeable population of ethnic Germans who often worked with the Axis powers, and the German Army recruited upwards of a million volunteers from occupied countries. The Soviet Union in particular had a number of Russia German enclaves across the region, that reached as far as the Volga river and Kazakhstan and numbered at several million people. In Russia, these communities had existed for centuries, but they were ostracized or mistrusted by Soviet leadership and the deaths of these communities under Stalin's regime is often considered genocide. In addition to ethnic Germans, collaborators also included large numbers of Eastern Europeans who sympathized with Nazi ideology, or were hostile to Soviet or communist expansion; this also included ethnic minorities, such as Muslims from the Balkans or USSR.

Collaborators in the West The perceived threat of communism in the west saw men volunteer from countries such as France, the Netherlands, or Norway, to fight in the Axis armies. The fluctuating borders of the interwar period also meant that there were many German communities across the borders of neighboring countries, whose men also enlisted in the Wehrmacht. Within these occupied countries, conspirators with local knowledge were used to track down Jews and political adversaries, and many collaborated in order to elevate their positions in the government or enterprises. Apart from Austria, however, the majority of the public in annexed territories were unsupportive or hostile to their occupiers, and after the war, many of the surviving collaborators were tried (and often executed) for their actions.

Germany DE: Population: Ages 0-14: % of Total Population data was reported at 11.360 % in 2021. This records an increase from the previous number of 11.280 % for 2020. Germany DE: Population: Ages 0-14: % of Total Population data is updated yearly, averaging 11.970 % from Dec 1990 (Median) to 2021, with 32 observations. The data reached an all-time high of 14.210 % in 1993 and a record low of 10.920 % in 2015. Germany DE: Population: Ages 0-14: % of Total Population 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.GGI: Social: Demography: OECD Member: Annual.

About this dataset

Context

The dataset tabulates the population of New Germany by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of New Germany across both sexes and to determine which sex constitutes the majority.

Key observations

There is a majority of male population, with 53.01% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the New Germany is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of New Germany total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for New Germany Population by Race & Ethnicity. You can refer the same here

Germany DE: Population: per 1 000 Inhabitants data was reported at 83,129.280 Person in 2021. This records a decrease from the previous number of 83,160.880 Person for 2020. Germany DE: Population: per 1 000 Inhabitants data is updated yearly, averaging 82,073.720 Person from Dec 1990 (Median) to 2021, with 32 observations. The data reached an all-time high of 83,160.880 Person in 2020 and a record low of 79,433.030 Person in 1990. Germany DE: Population: per 1 000 Inhabitants 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.GGI: Social: Demography: OECD Member: Annual.

Persons aged 18 to 49 living in private households at the timepoint of survey

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Germany township by race. It includes the distribution of the Non-Hispanic population of Germany township across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Germany township across relevant racial categories.

Key observations

Of the Non-Hispanic population in Germany township, the largest racial group is White alone with a population of 2,651 (97.28% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the Germany township
• Population: The population of the racial category (for Non-Hispanic) in the Germany township is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Germany township total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Germany township Population by Race & Ethnicity. You can refer the same here

In 2024, there were around 12.4 million employed people with a migration background living in Germany. According to the source, a person is considered as having a migration background when they or at least one parent do not have German citizenship by birth. This definition includes the following:1. Immigrated and non-immigrated foreigners.2. Immigrated and non-immigrated naturalized citizens.3. Late emigrants.4. Descendants born with German citizenship within the three groups named above.

Habitat and density effects on the demography of an expanding wolf population in Central Europe

https://doi.org/10.5061/dryad.dncjsxm5m

Tables containing the data used in the demographic analyses of the German wolf population.

Description of the data and file structure

Two tables are provided:

• data_wolf_survival_table.csv. This table contains individual information used in the survival analyses: information on the number of weeks an individual was alive (weeks_date) until confirmed death (status = 1) or went missing (censored, status = 0), sex, the month of the year that the individual was last detected (death_month), the season of the last detection, habitat suitability of the natal (hs_8km_natal) and final territories (hs_8km_final), the information to calculate the territory density in the 50 km buffer in the natal (_first) and final (_last) territories (nterr_buffer50 = the number of territories in buffer...

A collection of population life tables covering a multitude of countries and many years. Most of the HLD life tables are life tables for national populations, which have been officially published by national statistical offices. Some of the HLD life tables refer to certain regional or ethnic sub-populations within countries. Parts of the HLD life tables are non-official life tables produced by researchers. Life tables describe the extent to which a generation of people (i.e. life table cohort) dies off with age. Life tables are the most ancient and important tool in demography. They are widely used for descriptive and analytical purposes in demography, public health, epidemiology, population geography, biology and many other branches of science. HLD includes the following types of data: * complete life tables in text format; * abridged life tables in text format; * references to statistical publications and other data sources; * scanned copies of the original life tables as they were published. Three scientific institutions are jointly developing the HLD: the Max Planck Institute for Demographic Research (MPIDR) in Rostock, Germany, the Department of Demography at the University of California at Berkeley, USA and the Institut national d''��tudes d��mographiques (INED) in Paris, France. The MPIDR is responsible for maintaining the database.

Germany is a country known for immigration. In 2015, 21% of the general population in Germany consisted of individuals with a migration background. This article focuses on cancer-specific incidence and mortality among one of the biggest migrant groups in Germany: the resettlers. Resettlers are ethnic Germans who mainly immigrated from the Russian federation and other countries of the former Soviet Union after its collapse in 1989. We investigated differences between resettlers and the general German population, regarding (i) incidence and mortality of malignant neoplasms, (ii) time trends of the corresponding incidence and mortality, and (iii) cancer stage at diagnosis. We provide data from two resettler cohorts covering an observation time of 20 years: one cohort on cancer incidence (N = 32,972), and another cohort on mortality (N = 59,390). Cancer-specific standardized incidence ratios (SIR) and standardized mortality ratios (SMR) for all malignant neoplasms combined and the most common cancer-sites were calculated between resettlers and the general German population. Time trend analyses using Poisson regression were performed to investigate the developments of SIRs and SMRs. To investigate differences in stage at diagnosis, logistic regression was performed, calculating Odds Ratios for condensed cancer stages. We observed higher incidence and mortality of stomach cancer [SIR (men) 1.62, 95%CI 1.17–2.19; SMR (men) 1.62, 95%CI 1.31–2.01; SIR (women) 1.32, 95%CI 0.86–1.94; SMR (women) 1.52, 95%CI 1.19–1.93] and higher mortality of lung cancer [SMR (men) 1.34, 95%CI 1.20–1.50] among resettlers compared to the general German population, but lower incidence and mortality of colorectal (both sexes), lung (women), prostate and female breast cancer. However, time trend analyses showed converging incidence risks of cause-specific incidence over time, whereas differences of mortality did not show changes over time. Results from logistic regression suggest that resettler men were more often diagnosed with advanced cancer stages compared to the Münster population. Our findings suggest that risk factor patterns of the most common cancer-sites among resettlers are similar to those observed within the Russian population. Such increases in prostate, colorectal and breast cancer incidence may be the consequence of improved detection measures, and/or the adaptation of resettlers to the German lifestyle.

About this dataset

Context

The dataset presents the median household income across different racial categories in New Germany. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of New Germany population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 97.22% of the total residents in New Germany. Notably, the median household income for White households is $70,710. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $70,710.

https://i.neilsberg.com/ch/new-germany-mn-median-household-income-by-race.jpeg" alt="New Germany median household income diversity across racial categories">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in New Germany.
• Median household income: Median household income, adjusting for inflation, presented in 2022-inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for New Germany median household income by race. You can refer the same here

Behavioral trust conditional on individual- and zip-code-level indicators of socio-economic status and ethnic diversity.

The largest number of immigrants in Germany were from Ukraine, as of 2024. The top three origin countries were rounded up by Romania and Turkey. Immigrants are defined as having left a country, which may be their home country, to permanently reside in another. Upon arriving, immigrants do not hold the citizenship of the country they move to. Immigration in the EU All three aforementioned countries are members of the European Union, which means their citizens have freedom of movement between EU member states. In practice, this means that citizens of any EU member country may relocate between them to live and work there. Unrestricted by visas or residence permits, the search for university courses, jobs, retirement options, and places to live seems to be defined by an enormous amount of choice. However, even in this freedom of movement scheme, immigration may be hampered by bureaucratic hurdles or financial challenges. Prosperity with a question mark While Germany continues to be an attractive destination for foreigners both in and outside the European Union, as well as asylum applicants, it remains to be seen how current events might influence these patterns, whether the number of immigrants arriving from certain countries will shift. Europe’s largest economy is suffering. Climbing inflation levels in the last few months, as well as remaining difficulties from the ongoing coronavirus (COVID-19) pandemic are affecting global economic development. Ultimately, future immigrants may face the fact of moving from one struggling economy to another.