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...

In the past four centuries, the population of the Thirteen Colonies and United States of America has grown from a recorded 350 people around the Jamestown colony in Virginia in 1610, to an estimated 346 million in 2025. While the fertility rate has now dropped well below replacement level, and the population is on track to go into a natural decline in the 2040s, projected high net immigration rates mean the population will continue growing well into the next century, crossing the 400 million mark in the 2070s. Indigenous population Early population figures for the Thirteen Colonies and United States come with certain caveats. Official records excluded the indigenous population, and they generally remained excluded until the late 1800s. In 1500, in the first decade of European colonization of the Americas, the native population living within the modern U.S. borders was believed to be around 1.9 million people. The spread of Old World diseases, such as smallpox, measles, and influenza, to biologically defenseless populations in the New World then wreaked havoc across the continent, often wiping out large portions of the population in areas that had not yet made contact with Europeans. By the time of Jamestown's founding in 1607, it is believed the native population within current U.S. borders had dropped by almost 60 percent. As the U.S. expanded, indigenous populations were largely still excluded from population figures as they were driven westward, however taxpaying Natives were included in the census from 1870 to 1890, before all were included thereafter. It should be noted that estimates for indigenous populations in the Americas vary significantly by source and time period. Migration and expansion fuels population growth The arrival of European settlers and African slaves was the key driver of population growth in North America in the 17th century. Settlers from Britain were the dominant group in the Thirteen Colonies, before settlers from elsewhere in Europe, particularly Germany and Ireland, made a large impact in the mid-19th century. By the end of the 19th century, improvements in transport technology and increasing economic opportunities saw migration to the United States increase further, particularly from southern and Eastern Europe, and in the first decade of the 1900s the number of migrants to the U.S. exceeded one million people in some years. It is also estimated that almost 400,000 African slaves were transported directly across the Atlantic to mainland North America between 1500 and 1866 (although the importation of slaves was abolished in 1808). Blacks made up a much larger share of the population before slavery's abolition. Twentieth and twenty-first century The U.S. population has grown steadily since 1900, reaching one hundred million in the 1910s, two hundred million in the 1960s, and three hundred million in 2007. Since WWII, the U.S. has established itself as the world's foremost superpower, with the world's largest economy, and most powerful military. This growth in prosperity has been accompanied by increases in living standards, particularly through medical advances, infrastructure improvements, clean water accessibility. These have all contributed to higher infant and child survival rates, as well as an increase in life expectancy (doubling from roughly 40 to 80 years in the past 150 years), which have also played a large part in population growth. As fertility rates decline and increases in life expectancy slows, migration remains the largest factor in population growth. Since the 1960s, Latin America has now become the most common origin for migrants in the U.S., while immigration rates from Asia have also increased significantly. It remains to be seen how immigration restrictions of the current administration affect long-term population projections for the United States.

This data set shows the population trajectory for Sri Lanka (Ceylon) before, during, and after the influenza pandemic of 1918-19. Data covers the population estimates of all districts computed including data from the 1946 census as well as estimates of non-plantation districts computed including data from the 1946 census.

About this dataset

Context

The dataset tabulates the Great Falls population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Great Falls across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Great Falls was 1,927, a 0.47% increase year-by-year from 2022. Previously, in 2022, Great Falls population was 1,918, a decline of 0.88% compared to a population of 1,935 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Great Falls decreased by 253. In this period, the peak population was 2,180 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Great Falls is shown in this column.
• Year on Year Change: This column displays the change in Great Falls population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Great Falls Population by Year. You can refer the same here

In 1800, the present-day region of Mexico had a population of just over six million people. Mexico gained its independence from the Spanish crown in 1821, and population growth remained steady for the next 85 years. Growth then halted with with the Panic of 1907, an American financial crisis whose ripple effects in Mexico would set the stage for the Mexican Revolution in 1910. This revolution would see population flatline at just over fifteen million between 1910 and 1920, as widespread conflict and result in the death of between 1.7 to 2.7 million over the decade, and the coinciding 1918 Spanish Flu epidemic would see the loss of another 300,000 in this time period. Following the end of both the Mexican Revolution and the Spanish Flu epidemic in 1920, the population of Mexico would begin to increase rapidly as modernization would see mortality rates fall and standards of living rise throughout the country. This growth has continued steadily into the 21st century, and in 2020, Mexico is estimated to have a population of just under 129 million.

About this dataset

Context

The dataset tabulates the Monon population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Monon across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Monon was 1,938, a 1.04% increase year-by-year from 2022. Previously, in 2022, Monon population was 1,918, a decline of 0% compared to a population of 1,918 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Monon increased by 165. In this period, the peak population was 1,938 in the year 2023. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Monon is shown in this column.
• Year on Year Change: This column displays the change in Monon population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Monon Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Frankton population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Frankton across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Frankton was 1,791, a 0.56% increase year-by-year from 2021. Previously, in 2021, Frankton population was 1,781, an increase of 0.34% compared to a population of 1,775 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Frankton decreased by 123. In this period, the peak population was 1,918 in the year 2002. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Frankton is shown in this column.
• Year on Year Change: This column displays the change in Frankton population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Frankton Population by Year. You can refer the same here

This annual data set shows the population trajectory for Java, Indonesia before, during, and after the influenza pandemic of 1918-19. Data covers the population estimates computed with and without 1880 data. For additional information, please contact Siddharth Chandra at chandr45@msu.edu.

Chart and table of population level and growth rate for the state of Georgia from 1900 to 2024.

PERIOD: 1920-1939. NOTE: (As of October 1st but as of September 1st in 1923)The population estimates were obtained as follows: (1) For 1921 to 1923, the population estimate is the sum of county- and city-level population estimates obtained by multiplying the de facto population in the Population Census conducted on October 1, 1920, with the average annual population growth rate by gender from 1908 to 1918. (2) For 1924, the difference between the population of Japan overall calculated using the population growth rate by sex in each city and summing up the results and the population overall calculated using the population growth rate by sex for Japan overall was proportionally subtracted from the population of each prefecture; moreover, the population decrease due to the Great Kanto Earthquake on September 1, 1923 was also taken into account. (3) For Taisho 1926 to 1929, the de facto population in the 1920 and 1925 Population Censuses is used to obtain the annual average geometric growth rate of Japan's population overall, which is then used to estimate the population. (4) For 1931 to 1934, the same procedure is employed using the de facto population in the 1920 and 1930 Population Censuses. (5) From 1926 onward, the population estimates are obtained by adding the increase in the difference between births and deaths up to each estimation year in the 1935 Population Census using the results of the Vital Statistics survey. SOURCE: [Survey by the Statistics Bureau, Imperial Cabinet].

A key question in ecology is the relative impact of internal nonlinear dynamics and external perturbations on the long-term trajectories of natural systems. Measles has been analyzed extensively as a paradigm for consumer-resource dynamics due to the oscillatory nature of the host-pathogen life cycle, the abundance of rich data to test theory, and public health relevance. The dynamics of measles in London, in particular, has acted as a prototypical test bed for such analysis using incidence data from the pre-vaccination era (1944–1967). However, during this timeframe there were few external large-scale perturbations, limiting an assessment of the relative impact of internal and extra demographic perturbations to the host population. Here, we extended the previous London analyses to include nearly a century of data that also contains four major demographic changes: the First and Second World Wars, the 1918 influenza pandemic, and the start of a measles mass vaccination program. By combining mortality and incidence data using particle filtering methods, we show that a simple stochastic epidemic model, with minimal historical specifications, can capture the nearly 100 years of dynamics including changes caused by each of the major perturbations. We show that the majority of dynamic changes are explainable by the internal nonlinear dynamics of the system, tuned by demographic changes. In addition, the 1918 influenza pandemic and World War II acted as extra perturbations to this basic epidemic oscillator. Our analysis underlines that long-term ecological and epidemiological dynamics can follow very simple rules, even in a non-stationary population subject to significant perturbations and major secular changes.

Following the outbreak of the H1N1 influenza pandemic of 1918, which came to be known as the Spanish Flu, the number of deaths due to influenza and pneumonia soared. Pneumonia was caused either by the influenza or by a bacterial superinfection that took hold due to the patient's weakened state as a result of the influenza, for this reason, influenza deaths and pneumonia deaths were recorded together as one. Pennsylvania had the highest mortality rate due to the pandemic, where there were over 880 fatalities per 100,000 people; meaning that approximately 0.9 percent of the state's population died from the Spanish Flu pandemic in 1918.

When compared with the 1915 mortality rates, many states, such as California and Pennsylvania, saw their mortality rate due to influenza and pneumonia increase five-fold by 1818, which was the worst year of the pandemic. While the mortality rate decreased significantly in the year 1919, there was no US state where it fell to it's pre-pandemic level, and the 1919 mortality rate was still double the pre-pandemic rate in some states such as California, South Carolina and Washington.

How did the 1918 influenza pandemic affect female labor force participation in India over the short run and the medium run? We use an event-study approach at the district level and four waves of decadal census data in order to answer this question. We find that districts most adversely affected by influenza mortality saw a temporary increase in female labor force participation in 1921, an increase that was concentrated in the service sector. We find suggestive evidence that distress labor supply by widows and rising wages help account for this result.

About this dataset

Context

The dataset tabulates the Everett population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Everett across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Everett was 1,746, a 0.40% decrease year-by-year from 2022. Previously, in 2022, Everett population was 1,753, a decline of 0.34% compared to a population of 1,759 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Everett decreased by 157. In this period, the peak population was 1,918 in the year 2001. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Everett is shown in this column.
• Year on Year Change: This column displays the change in Everett population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Everett Population by Year. You can refer the same here

This data set contains the number of deaths per thousand population in periods of four weeks between 1916 and 1920 in the regencies of Java, Indonesia. The increased number of deaths in late 1918 and early 1919 is due to the influenza Pandemic of 1918-19 in Indonesia. Indonesian mortality rates from influenza, 1916-1920.

Social factors have been shown to create differential burden of influenza across different geographic areas. We explored the relationship between potential aggregate-level social determinants and mortality during the 1918 influenza pandemic in Chicago using a historical dataset of 7,971 influenza and pneumonia deaths. Census tract-level social factors, including rates of illiteracy, homeownership, population, and unemployment, were assessed as predictors of pandemic mortality in Chicago. Poisson models fit with generalized estimating equations (GEEs) were used to estimate the association between social factors and the risk of influenza and pneumonia mortality. The Poisson model showed that influenza and pneumonia mortality increased, on average, by 32.2% for every 10% increase in illiteracy rate adjusted for population density, homeownership, unemployment, and age. We also found a significant association between transmissibility and population density, illiteracy, and unemployment but not homeownership. Lastly, analysis of the point locations of reported influenza and pneumonia deaths revealed fine-scale spatiotemporal clustering. This study shows that living in census tracts with higher illiteracy rates increased the risk of influenza and pneumonia mortality during the 1918 influenza pandemic in Chicago. Our observation that disparities in structural determinants of neighborhood-level health lead to disparities in influenza incidence in this pandemic suggests that disparities and their determinants should remain targets of research and control in future pandemics.

This project contains a city-level panel dataset of deaths-by-cause from the U.S. Census Bureau for the years 1915 to 1938, annually, as reported in the publication “Mortality Statistics.” For some cities, the data is available separately for white and non-white deaths. This data is based on transcripts of death certificates received by the Census Bureau from certain areas of the country called “registration areas.” In 1918, the data covers an estimated population of 82,091,523, or 77.8% total estimated population of the United States, and includes 30 states, the District of Columbia, and 27 cities in nonregistration states. States and cities are added over time, so the panel is not complete. When data is reported based on white and non-white deaths, the majority (95%+) are Blacks (1918, page 11).

Sources: Scientific Publications; official Statistics:

Max Broesike (1904), Rückblick auf die Entwicklung der preußischen Bevölkerung von 1875 bis 1900, Preußische Statistik 188, S. 12-14.

Elsner/Lehmann (1988): Ausländische Arbeiter unter dem deutschen Imperialismus, 1900 bis 1985. Berlin: Dietz Verlag.

Hubert, Michel (1998): Deutschland im Wandel. Geschichte der deutschen Bevölkerung seit 1815. Stuttgart: Steiner.

Köbler, Gerhard (2007): Historisches Lexikon der deutschen Länder. Die deutschen Territorien vom Mittelalter bis zur Gegenwart. München: Beck.

Königlich Preußisches Statistisches Landesamt: Statistisches Jahrbuch für den Preußischen Staat, 13. Jahrgang, Berlin 1916 und 16. Jahrgang, Berlin 1920.

Königlich Statistisches Bureau in Berlin: Preußische Statistik (Amtliches Quellenwerk), Heft 139. Die Sterblichkeit nach Todesursachen und Altersklassen der Gestorbenen sowie die Selbstmorde und die tödlichen Verunglückungen im preußischen Staate während des Jahres 1894. Berlin, 1896.

Königlich Statistisches Bureau in Berlin: Preußische Statistik, Heft 188: Rückblick auf die Entwicklung der preußischen Bevölkerung von 1875 bis 1900. Berlin, 1904, S. 105.

Oltmer, Jochen (2005): Migration und Politik in der Weimarer Republik. Göttingen: Vandenhoeck&Ruprecht.

Preußisches Statistisches Landesamt: Statistisches Jahrbuch für den Freistaat Preußen, Statistisches Jahrbuch für den Freistaat Preußen, 17. Band, 1921 und 29. Band, 1933.

Stat. Bundesamt (Hrsg.): Bevölkerung und Erwerbstätigkeit. Fachserie 1, Reihe 2. Ausländische Bevölkerung. Ausgabe 2013, S. 26, Tabelle 1.

Stat. Reichsamt (Hrsg.): Statistisches Jahrbuch für das Deutsche Reich, verschiedene Jahrgänge: Jg. 1880 bis Jg. 1941/42.

Stat. Reichsamt (Hrsg.): Statistik des Deutschen Reichs: Band 360, Band 393, Band 441.

Trevisiol, O.: Die Einbürgerungspraxis im Deutschen Reich 1871-1945. Diss. 2004. Tab. 1, S. 20 und Tab. 4, S. 24. KOPS – Das institutionelle Repositorium der Universität Konstanz, Suche im Bestand ‘Geschichte und Soziologie‘, WEB: http://d-nb.info/974206237/34

Further literature

Bade, Klaus J. (2002): Europa in Bewegung. Migration vom späten 18. Jahrhundert bis zur Gegenwart. München: Beck.

Gosewinkel, Dieter (2001): Einbürgern und Ausschließen. Göttingen: Vandenhoeck & Ruprecht.

Oltmer, Jochen (2012): Globale Migration. Geschichte und Gegenwart. München: Beck.

Oltmer, Jochen (2013): Migration im 19. Und 20. Jahrhundert. München: Oldenbourg.

wikipedia.org

Hungary: Transleithania was the Hungarian-ruled section of the Austro-Hungarian Empire, which controlled much of Central Europe from 1867 to 1918. This graphic shows the total population of Hungary: Transleithania from 1850 until 1910, just before the outbreak of World War I. As we can see from the graph, the population grows rather gradually throughout this 60 year period. The population begins at 13.2 million people in 1850, and then rises gradually to 20.9 million in 1910, just 4 years before the empire declares war on Serbia, which would develop into the First World War. As mentioned, the population rises gradually, although it does slow quite noticeably between 1869 and 1880, this is because of the data collecting methods of the time, as the earlier entries did not include military personnel. This also influences the data relating to gender, as the balance between the number of men and women fluctuates throughout this time. From 1880 onwards, the population of Transleithania enjoyed healthy growth due to increased industrialization and standard of living.

About this dataset

Context

The dataset tabulates the Rolling Hills population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Rolling Hills across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Rolling Hills was 1,644, a 1.38% decrease year-by-year from 2022. Previously, in 2022, Rolling Hills population was 1,667, a decline of 1.83% compared to a population of 1,698 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Rolling Hills decreased by 233. In this period, the peak population was 1,918 in the year 2005. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Rolling Hills is shown in this column.
• Year on Year Change: This column displays the change in Rolling Hills population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Rolling Hills Population by Year. You can refer the same here