About this dataset

Context

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

Key observations

Of the Non-Hispanic population in Italy, the largest racial group is White alone with a population of 1,375 (72.98% 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 Italy
• Population: The population of the racial category (for Non-Hispanic) in the Italy is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Italy 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 Italy Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

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

Key observations

The percent distribution of Italy town population by race (across all racial categories recognized by the U.S. Census Bureau): 96.36% are white, 1.15% are American Indian and Alaska Native and 2.49% are multiracial.

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 (excluding ethnicity) for the Italy town
• Population: The population of the racial category (excluding ethnicity) in the Italy town is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Italy town 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 Italy town Population by Race & Ethnicity. You can refer the same here

At the beginning of the 19th century, the area of modern-day Italy, at the time a collection of various states and kingdoms, was estimated to have a population of nineteen million, a figure which would grow steadily throughout the century, and by the establishment of the Kingdom of Italy in 1861, the population would rise to just over 26 million.

Italy’s population would see its first major disruption during the First World War, as Italy would join the Allied Forces in their fight against Austria-Hungary and Germany. In the First World War, Italy’s population would largely stagnate at 36 million, only climbing again following the end of the war in 1920. While Italy would also play a prominent role in the Second World War, as the National Fascist Party-led country would fight alongside Germany against the Allies, Italian fatalities from the war would not represent a significant percentage of Italy’s population compared to other European countries in the conflict. As a result, Italy would exit the Second World War with a population of just over 45 million.

From this point onwards the Italian economy started to recover from the war, and eventually boomed, leading to increased employment and standards of living, which facilitated steady population growth until the mid-1980s, when falling fertility and birth rates would cause growth to largely cease. From this point onward, the Italian population would remain at just over 57 million, until the 2000s when it began growing again due to an influx of migrants, peaking in 2017 at just over 60 million people. In the late 2010s, however, the Italian population began declining again, as immigration slowed and the economy weakened. As a result, in 2020, Italy is estimated to have fallen to a population of 59 million.

In 2024, Italy’s resident population is estimated to be almost 59 million inhabitants. About one-sixth of them lived in Lombardy, the most populous region in the country. Lazio and Campania followed, with roughly 5.7 million and 5.6 million inhabitants, respectively. These figures are mainly driven by Rome and Naples, the administrative capitals of these regions, and two of the largest metropolitan areas in the country. Which region has the oldest population?  The population in Italy has become older and older over the last years. The average age in the country is equal to 46.6 years, but in some regions this figure is even higher. Liguria records an average age of 49.5 years and has one of the lowest birth rates in the country. Demographic trends for the future Liguria’s case, however, is not an outlier. Italy is already the country with the highest share of old people in Europe. At the same time, the very low number of new births means that, despite an always-increasing life expectancy, the Italian population is declining. Indeed, projections estimate that the country will have five million fewer inhabitants by 2050.

About this dataset

Context

The dataset tabulates the Italy town Hispanic or Latino population. It includes the distribution of the Hispanic or Latino population, of Italy town, by their ancestries, as identified by the Census Bureau. The dataset can be utilized to understand the origin of the Hispanic or Latino population of Italy town.

Key observations

Among the Hispanic population in Italy town, regardless of the race, the largest group is of Mexican origin, with a population of 8 (100% of the total 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.

Origin for Hispanic or Latino population include:

• Mexican
• Puerto Rican
• Cuban
• Other Hispanic or Latino

Variables / Data Columns

• Origin: This column displays the origin for Hispanic or Latino population for the Italy town
• Population: The population of the specific origin for Hispanic or Latino population in the Italy town is shown in this column.
• % of Total Hispanic Population: This column displays the percentage distribution of each Hispanic origin as a proportion of Italy town total Hispanic or Latino 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 Italy town Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset presents the median household income across different racial categories in Italy town. 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 Italy town population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 96.36% of the total residents in Italy town. Notably, the median household income for White households is $58,125. Interestingly, despite the White population being the most populous, it is worth noting that Two or More Races households actually reports the highest median household income, with a median income of $78,750. This reveals that, while Whites may be the most numerous in Italy town, Two or More Races households experience greater economic prosperity in terms of median household income.

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 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 Italy town.
• Median household income: Median household income, adjusting for inflation, presented in 2023-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 Italy town median household income by race. You can refer the same here

As of January 2024, Italy had a population of around 59 million people. Over the past years, Italy's population experienced a decrease. An aging population and a very low birth rate are the main causes of such a contraction. Population forecasts predict that the number of residents in the country will be roughly 52.3 million by 2050. Birth rates and foreign population The birth rate in Italy declined continuously from 2002, when 9.4 babies per 1,000 inhabitants were born, to 2023, when this number dropped to 6.4. However, there was one increasing demographic trend in the country over the last years. The foreign-born population, in fact, increased from 2009 to 2022, surpassing six million people. Regional and gender distribution In Italy, female citizens were slightly more numerous than their male counterparts. The most populated region in 2024 was Lombardy, accounting for a sixth of the whole Italian population. Lazio and Campania followed, both around 5.6 million inhabitants. On the other hand, the smallest Italian region in terms of population was Aosta Valley, with only around 123,000 inhabitants.

Projections published in 2022 estimated that the population in Italy will decrease in the following years. In January 2024, the Italian population added up to 59 million people, but in 2030 Italians will be 57.5 million individuals. Twenty years later, the population will be around 52.3 million people. Low birth rate and old population The birth rate in Italy has constantly dropped in the last years. In 2023, 6.4 children were born per 1,000 inhabitants, three babies less than in 2002. Nationwide, the highest number of births was registered in the southern regions, whereas central Italy had the lowest number of children born every 1,000 people. More specifically, the birth rate in the south stood at 7 infants, while in the center it was equal to 5.9 births. Consequently, the population in Italy has aged over the last decade. Between 2002 and 2024, the age distribution of the Italian population showed a growing share of people aged 65 years and older. As a result, the share of young people decreased. The European exception Similarly, the population in Europe is estimated to decrease in the coming years. In 2024, there were 740 million people living in Europe. In 2100, the figure is expected to drop to 586 million inhabitants. However, projections of the world population suggest that Europe might be the only continent experiencing a population decrease. For instance, the population in Africa could grow from 1.41 billion people in 2022 to 3.92 billion individuals in 2100, the fastest population growth worldwide.

In the past years, the share of people aged over 65 years grew constantly in Italy. Estimates for 2024 report that 24.3 percent of the Italian inhabitants are aged 65 years and older. Moreover, 63.5 percent of the residents are predicted to be aged between 15 and 64 years and only 12.2 percent to be 14 years old and younger. In 2023, the Italian region with the highest proportion of kids up to 14 years old was Trentino-South Tyrol, with 14.4 percent. On the other hand, 28.9 percent of the people in Liguria were over 65 years, making it the region with the highest share of elderly among its residents. Causes of an aging population The growing proportion of old people in Italy is due to two main factors. First, the birth rate in the country decreased over the past years. In 2023, less than seven children were born per 1,000 inhabitants, two fewer infants than in 2002. Second, life expectancy increased over the same period. A 65-year-old Italian woman could expect to have almost 21 more years of life ahead in 2002, while by 2023 this number reached 22.4. The increase for men was even greater, with male life expectancy at 65 growing from around 17 years in 2002 to 19.5 years in 2023. Future demographic trends The aging trend in the Italian population is not expected to change in the upcoming years. Projections made in 2022 predicted that the country's population is going to sensibly decrease in numbers. Population forecasts for 2050 account for slightly more than 52 million citizens, around seven million fewer compared to 2020.

The dataset contains data from the 13th General Population Census relating to the resident population, which is made up of people who habitually reside in the Municipality and are present there on the date of the census and by people who also habitually reside in the Municipality, but who on the date of the census resulted because they were temporarily present in another Italian municipality or abroad. The following support tables are also available in the dataset: * Descriptions of the columns * Decodes of the codes contained in the columns. The table linking the Census Sections and territorial divisions is available at the following link: https://dati.comune.milano.it/dataset/ds1635-censimento-1991-sezioni-di-censimento-associazione-tra-sezioni-e -territorial-divisions

A data set of cross-nationally comparable microdata samples for 15 Economic Commission for Europe (ECE) countries (Bulgaria, Canada, Czech Republic, Estonia, Finland, Hungary, Italy, Latvia, Lithuania, Romania, Russia, Switzerland, Turkey, UK, USA) based on the 1990 national population and housing censuses in countries of Europe and North America to study the social and economic conditions of older persons. These samples have been designed to allow research on a wide range of issues related to aging, as well as on other social phenomena. A common set of nomenclatures and classifications, derived on the basis of a study of census data comparability in Europe and North America, was adopted as a standard for recoding. This series was formerly called Dynamics of Population Aging in ECE Countries. The recommendations regarding the design and size of the samples drawn from the 1990 round of censuses envisaged: (1) drawing individual-based samples of about one million persons; (2) progressive oversampling with age in order to ensure sufficient representation of various categories of older people; and (3) retaining information on all persons co-residing in the sampled individual''''s dwelling unit. Estonia, Latvia and Lithuania provided the entire population over age 50, while Finland sampled it with progressive over-sampling. Canada, Italy, Russia, Turkey, UK, and the US provided samples that had not been drawn specially for this project, and cover the entire population without over-sampling. Given its wide user base, the US 1990 PUMS was not recoded. Instead, PAU offers mapping modules, which recode the PUMS variables into the project''''s classifications, nomenclatures, and coding schemes. Because of the high sampling density, these data cover various small groups of older people; contain as much geographic detail as possible under each country''''s confidentiality requirements; include more extensive information on housing conditions than many other data sources; and provide information for a number of countries whose data were not accessible until recently. Data Availability: Eight of the fifteen participating countries have signed the standard data release agreement making their data available through NACDA/ICPSR (see links below). Hungary and Switzerland require a clearance to be obtained from their national statistical offices for the use of microdata, however the documents signed between the PAU and these countries include clauses stipulating that, in general, all scholars interested in social research will be granted access. Russia requested that certain provisions for archiving the microdata samples be removed from its data release arrangement. The PAU has an agreement with several British scholars to facilitate access to the 1991 UK data through collaborative arrangements. Statistics Canada and the Italian Institute of statistics (ISTAT) provide access to data from Canada and Italy, respectively. * Dates of Study: 1989-1992 * Study Features: International, Minority Oversamples * Sample Size: Approx. 1 million/country Links: * Bulgaria (1992), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/02200 * Czech Republic (1991), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06857 * Estonia (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06780 * Finland (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06797 * Romania (1992), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06900 * Latvia (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/02572 * Lithuania (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03952 * Turkey (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03292 * U.S. (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06219

Abstract

Different countries have different health outcomes that are in part due to the way respective health systems perform. Regardless of the type of health system, individuals will have health and non-health expectations in terms of how the institution responds to their needs. In many countries, however, health systems do not perform effectively and this is in part due to lack of information on health system performance, and on the different service providers.

The aim of the WHO World Health Survey is to provide empirical data to the national health information systems so that there is a better monitoring of health of the people, responsiveness of health systems and measurement of health-related parameters.

The overall aims of the survey is to examine the way populations report their health, understand how people value health states, measure the performance of health systems in relation to responsiveness and gather information on modes and extents of payment for health encounters through a nationally representative population based community survey. In addition, it addresses various areas such as health care expenditures, adult mortality, birth history, various risk factors, assessment of main chronic health conditions and the coverage of health interventions, in specific additional modules.

The objectives of the survey programme are to: 1. develop a means of providing valid, reliable and comparable information, at low cost, to supplement the information provided by routine health information systems. 2. build the evidence base necessary for policy-makers to monitor if health systems are achieving the desired goals, and to assess if additional investment in health is achieving the desired outcomes. 3. provide policy-makers with the evidence they need to adjust their policies, strategies and programmes as necessary.

Geographic coverage

The survey sampling frame must cover 100% of the country's eligible population, meaning that the entire national territory must be included. This does not mean that every province or territory need be represented in the survey sample but, rather, that all must have a chance (known probability) of being included in the survey sample.

There may be exceptional circumstances that preclude 100% national coverage. Certain areas in certain countries may be impossible to include due to reasons such as accessibility or conflict. All such exceptions must be discussed with WHO sampling experts. If any region must be excluded, it must constitute a coherent area, such as a particular province or region. For example if ¾ of region D in country X is not accessible due to war, the entire region D will be excluded from analysis.

Analysis unit

Households and individuals

Universe

The WHS will include all male and female adults (18 years of age and older) who are not out of the country during the survey period. It should be noted that this includes the population who may be institutionalized for health reasons at the time of the survey: all persons who would have fit the definition of household member at the time of their institutionalisation are included in the eligible population.

If the randomly selected individual is institutionalized short-term (e.g. a 3-day stay at a hospital) the interviewer must return to the household when the individual will have come back to interview him/her. If the randomly selected individual is institutionalized long term (e.g. has been in a nursing home the last 8 years), the interviewer must travel to that institution to interview him/her.

The target population includes any adult, male or female age 18 or over living in private households. Populations in group quarters, on military reservations, or in other non-household living arrangements will not be eligible for the study. People who are in an institution due to a health condition (such as a hospital, hospice, nursing home, home for the aged, etc.) at the time of the visit to the household are interviewed either in the institution or upon their return to their household if this is within a period of two weeks from the first visit to the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING GUIDELINES FOR WHS

Surveys in the WHS program must employ a probability sampling design. This means that every single individual in the sampling frame has a known and non-zero chance of being selected into the survey sample. While a Single Stage Random Sample is ideal if feasible, it is recognized that most sites will carry out Multi-stage Cluster Sampling.

The WHS sampling frame should cover 100% of the eligible population in the surveyed country. This means that every eligible person in the country has a chance of being included in the survey sample. It also means that particular ethnic groups or geographical areas may not be excluded from the sampling frame.

The sample size of the WHS in each country is 5000 persons (exceptions considered on a by-country basis). An adequate number of persons must be drawn from the sampling frame to account for an estimated amount of non-response (refusal to participate, empty houses etc.). The highest estimate of potential non-response and empty households should be used to ensure that the desired sample size is reached at the end of the survey period. This is very important because if, at the end of data collection, the required sample size of 5000 has not been reached additional persons must be selected randomly into the survey sample from the sampling frame. This is both costly and technically complicated (if this situation is to occur, consult WHO sampling experts for assistance), and best avoided by proper planning before data collection begins.

All steps of sampling, including justification for stratification, cluster sizes, probabilities of selection, weights at each stage of selection, and the computer program used for randomization must be communicated to WHO

STRATIFICATION

Stratification is the process by which the population is divided into subgroups. Sampling will then be conducted separately in each subgroup. Strata or subgroups are chosen because evidence is available that they are related to the outcome (e.g. health, responsiveness, mortality, coverage etc.). The strata chosen will vary by country and reflect local conditions. Some examples of factors that can be stratified on are geography (e.g. North, Central, South), level of urbanization (e.g. urban, rural), socio-economic zones, provinces (especially if health administration is primarily under the jurisdiction of provincial authorities), or presence of health facility in area. Strata to be used must be identified by each country and the reasons for selection explicitly justified.

Stratification is strongly recommended at the first stage of sampling. Once the strata have been chosen and justified, all stages of selection will be conducted separately in each stratum. We recommend stratifying on 3-5 factors. It is optimum to have half as many strata (note the difference between stratifying variables, which may be such variables as gender, socio-economic status, province/region etc. and strata, which are the combination of variable categories, for example Male, High socio-economic status, Xingtao Province would be a stratum).

Strata should be as homogenous as possible within and as heterogeneous as possible between. This means that strata should be formulated in such a way that individuals belonging to a stratum should be as similar to each other with respect to key variables as possible and as different as possible from individuals belonging to a different stratum. This maximises the efficiency of stratification in reducing sampling variance.

MULTI-STAGE CLUSTER SELECTION

A cluster is a naturally occurring unit or grouping within the population (e.g. enumeration areas, cities, universities, provinces, hospitals etc.); it is a unit for which the administrative level has clear, nonoverlapping boundaries. Cluster sampling is useful because it avoids having to compile exhaustive lists of every single person in the population. Clusters should be as heterogeneous as possible within and as homogenous as possible between (note that this is the opposite criterion as that for strata). Clusters should be as small as possible (i.e. large administrative units such as Provinces or States are not good clusters) but not so small as to be homogenous.

In cluster sampling, a number of clusters are randomly selected from a list of clusters. Then, either all members of the chosen cluster or a random selection from among them are included in the sample. Multistage sampling is an extension of cluster sampling where a hierarchy of clusters are chosen going from larger to smaller.

In order to carry out multi-stage sampling, one needs to know only the population sizes of the sampling units. For the smallest sampling unit above the elementary unit however, a complete list of all elementary units (households) is needed; in order to be able to randomly select among all households in the TSU, a list of all those households is required. This information may be available from the most recent population census. If the last census was >3 years ago or the information furnished by it was of poor quality or unreliable, the survey staff will have the task of enumerating all households in the smallest randomly selected sampling unit. It is very important to budget for this step if it is necessary and ensure that all households are properly enumerated in order that a representative sample is obtained.

It is always best to have as many clusters in the PSU as possible. The reason for this is that the fewer the number of respondents in each PSU, the lower will be the clustering effect which

Rome is the most populous city in Italy. With 2.75 million inhabitants, the capital of the country put ahead Milan and Naples. Compared to the number of citizens in 2012, the resident population of Rome increased by over 140,000 individuals. Regional data Rome is located in the center of Italy in the Lazio region. Lazio is the second-largest region in terms of population size after Lombardy. In 2024, the region counts roughly 5.7 million inhabitants, whereas Lombardy has over ten million individuals. The third-largest region is Campania, with 5.6 million people. Naples, the major center of Campania, has around 910,000 inhabitants at the beginning of 2024. Nevertheless, this city was, back in the 19th century, one of the largest cities in Western Europe. Tourism in Rome The Eternal City is also the main tourist destination in Italy and was the eighth most-visited city in Europe. The largest groups of international visitors in Rome came from the United States of America, Japan, and the United Kingdom. Every year, more and more tourists also enjoy the best-known tourist attractions in Rome, like the Colosseum, the Roman Forum, and the Palatine Hill, which together recorded almost ten million visitors in 2022.

The dataset contains data from the 14th General Population Census relating to housing. A dwelling is defined as accommodation consisting of a single room or a set of rooms (rooms and ancillary rooms): * built with those requirements that make it suitable as a permanent residence for one or more people, even if one part is used as an office (professional studio, etc.), * equipped with at least one independent access from the outside (road, courtyard, etc.), which does not involve passing through other houses, or from common hallway spaces (landings, galleries, terraces, etc.), * separated from other housing units by walls, * inserted in a building. The following support tables are also available in the dataset: * Descriptions of the columns * Decodes of the codes contained in the columns. Other supporting tables are available at the following links: * Codes of the Italian Municipalities https://dati.comune.milano.it/dataset/ds1527-censimento-2001-comuni-italiani * Codes of the Italian Provinces https://dati.comune .milano.it/dataset/ds1528-censimento-2001-province-italiane * Connection between Census Sections and territorial divisions https://dati.comune.milano.it/dataset/ds1529-censimento-2001-sezioni

The dataset contains data from the 14th General Population Census relating to occupied homes, which are defined as homes where people live permanently, unlike unoccupied homes (empty for various reasons: vacant, second homes, etc.). The following support tables are also available in the dataset: * Descriptions of the columns * Decodes of the codes contained in the columns. Other supporting tables are available at the following links: * Codes of the Italian Municipalities https://dati.comune.milano.it/dataset/ds1527-censimento-2001-comuni-italiani * Codes of the Italian Provinces https://dati.comune .milano.it/dataset/ds1528-censimento-2001-province-italiane * Connection between Census Sections and territorial divisions https://dati.comune.milano.it/dataset/ds1529-censimento-2001-sezioni

About this dataset

Context

The dataset tabulates the Italy population by race and ethnicity. The dataset can be utilized to understand the racial distribution of Italy.

Content

The dataset will have the following datasets when applicable

Please note that in case when either of Hispanic or Non-Hispanic population doesnt exist, the respective dataset will not be available (as there will not be a population subset applicable for the same)

• Italy, TX Population Breakdown by Race
• Italy, TX Non-Hispanic Population Breakdown by Race
• Italy, TX Hispanic or Latino Population Distribution by Their Ancestries

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/.

About this dataset

Context

The dataset tabulates the Italy median household income by race. The dataset can be utilized to understand the racial distribution of Italy income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Italy, TX median household income breakdown by race betwen 2011 and 2021
• Median Household Income by Racial Categories in Italy, TX (2021, 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/.

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Explore our comprehensive data analysis and visual representations for a deeper understanding of Italy median household income by race. You can refer the same here

Prior to 1829, the area of modern day Greece was largely under the control of the Ottoman Empire. In 1821, the Greeks declared their independence from the Ottomans, and achieved it within 8 years through the Greek War of Independence. The Independent Kingdom of Greece was established in 1829 and made up the southern half of present-day, mainland Greece, along with some Mediterranean islands. Over the next century, Greece's borders would expand and readjust drastically, through a number of conflicts and diplomatic agreements; therefore the population of Greece within those political borders** was much lower than the population in what would be today's borders. As there were large communities of ethnic Greeks living in neighboring countries during this time, particularly in Turkey, and the data presented here does not show the full extent of the First World War, Spanish Flu Pandemic and Greko-Turkish War on these Greek populations. While it is difficult to separate the fatalities from each of these events, it is estimated that between 500,000 and 900,000 ethnic Greeks died at the hands of the Ottomans between the years 1914 and 1923, and approximately 150,000 died due to the 1918 flu pandemic. These years also saw the exchange of up to one million Orthodox Christians from Turkey to Greece, and several hundred thousand Muslims from Greece to Turkey; this exchange is one reason why Greece's total population did not change drastically, despite the genocide, displacement and demographic upheaval of the 1910s and 1920s. Greece in WWII A new Hellenic Republic was established in 1924, which saw a decade of peace and modernization in Greece, however this was short lived. The Greek monarchy was reintroduced in 1935, and the prime minister, Ioannis Metaxas, headed a totalitarian government that remained in place until the Second World War. Metaxas tried to maintain Greek neutrality as the war began, however Italy's invasion of the Balkans made this impossible, and the Italian army tried invading Greece via Albania in 1940. The outnumbered and lesser-equipped Greek forces were able to hold off the Italian invasion and then push them backwards into Albania, marking the first Allied victory in the war. Following a series of Italian failures, Greece was eventually overrun when Hitler launched a German and Bulgarian invasion in April 1941, taking Athens within three weeks. Germany's involvement in Greece meant that Hitler's planned invasion of the Soviet Union was delayed, and Hitler cited this as the reason for it's failure (although most historians disagree with this). Over the course of the war approximately eight to eleven percent of the Greek population died due to fighting, extermination, starvation and disease; including over eighty percent of Greece's Jewish population in the Holocaust. Following the liberation of Greece in 1944, the country was then plunged into a civil war (the first major conflict of the Cold War), which lasted until 1949, and saw the British and American-supported government fight with Greek communists for control of the country. The government eventually defeated the Soviet-supported communist forces, and established American influence in the Aegean and Balkans throughout the Cold War. Post-war Greece From the 1950s until the 1970s, the Marshall Plan, industrialization and an emerging Tourism sector helped the Greek economy to boom, with one of the strongest growth rates in the world. Apart from the military coup, which ruled from 1967 to 1974, Greece remained relatively peaceful, prosperous and stable throughout the second half of the twentieth century. The population reached 11.2 million in the early 2000s, before going into decline for the past fifteen years. This decline came about due to a negative net migration rate and slowing birth rate, ultimately facilitated by the global financial crisis of 2007 and 2008; many Greeks left the country in search of work elsewhere, and the economic troubles have impacted the financial incentives that were previously available for families with many children. While the financial crisis was a global event, Greece was arguably the hardest-hit nation during the crisis, and suffered the longest recession of any advanced economy. The financial crisis has had a consequential impact on the Greek population, which has dropped by 800,000 in 15 years, and the average age has increased significantly, as thousands of young people migrate in search of employment.

The Italian city of Venice was one of the largest cities in medieval and Renaissance era Europe. It was the center of the Republic of Venice, a maritime empire in the Mediterranean, and had one of Europe's largest ports for exotic goods (particularly from Asia), or luxury goods such as glassware. Impact of plague While its population was relatively small by modern standards, it is believed that Venice was among the five most populous cities in Western Europe in the given years between 1050 and 1650. The city's population did fluctuate over time due to devastating pandemics, and it is believed that Venice was one of the main points of entry for the Black Death in Europe. Venice was one of the hardest-hit cities during the Black Death; estimates fluctuate greatly across sources, but it is believed that the city lost around 40 percent of its population during the initial outbreak in the 1340s. Decline Furthermore, Venice lost roughly a third of its population during further plague pandemics (both introduced via war) in the 1570s and 1630s. Because of this, the population was kept fairly consistent across the given years between 1600 and 1800. The 18th century also saw the decline of the Venetian Empire, as other states gained power and influence in the Mediterranean. Venice also lost its importance as the entry point of exotic goods into Europe, as other European powers had already established their own maritime empires and trade routes across the globe. Eventually, the crumbling Venetian Empire fell to Napoleon in 1796, and its overseas territories were gradually taken by or split among various other powers. While the empire fell, the city itself continued to be a center for art and culture in Europe, and it has maintained this status until today. In 2021, Venice had a population of more than 250,000 people.

Migrants from the United Kingdom have long been Australia’s primary immigrant group and in 2023 there were roughly 960 thousand English-born people living in Australia. India and China held second and third place respectively with regard to Australia’s foreign-born population. The relative dominance of Asian countries in the list of top ten foreign-born residents of Australia represents a significant shift in Australia’s immigration patterns over the past few decades. Where European-born migrants had previously overshadowed other migrant groups, Australian migration figures are now showing greater migration numbers from neighboring countries in Asia and the Pacific. A history of migration Australia is often referred to as an ‘immigrant nation’, alongside the United States, Canada, and New Zealand. Before the Second World War, migrants to Australia were almost exclusively from the UK, however after 1945, Australia’s immigration policy was broadened to attract economic migrants and temporary skilled migrants. These policy changes saw and increase in immigrants particularly from Greece and Italy. Today, Australia maintains its status as an ‘’Immigrant nation’’, with almost 30 percent of the population born overseas and around 50 percent of the population having both that were born overseas. Australian visas The Australian immigration program has two main categories of visa, permanent and temporary. The permanent visa category offers three primary pathways: skilled, family and humanitarian. The skilled visa category is by far the most common, with more than a million permanent migrants living in Australia on this visa category at the last Australian census in 2021. Of the temporary visa categories, the higher education visa is the most popular, exceeding 180 thousand arrivals in 2023.