This dataset provides a historical overview of key global indicators, including Gross Domestic Product (GDP), population growth, and CO2 emissions. It captures economic trends, demographic shifts, and environmental impacts over multiple decades, making it useful for researchers, analysts, and policymakers.

The dataset includes Real GDP (inflation-adjusted), allowing for economic trend analysis while accounting for inflation effects. Additionally, it incorporates CO2 emissions data, enabling studies on the relationship between economic growth and environmental impact.

This dataset is valuable for multiple research areas:

✅ Macroeconomic Analysis – Study global economic growth, recessions, and recovery trends.

✅ Inflation & Monetary Policy – Compare nominal vs. real GDP to assess inflationary trends.

✅ Climate Change Research – Analyze CO2 emissions alongside economic growth to identify sustainability challenges.

✅ Predictive Modeling – Train machine learning models for forecasting GDP, population, or emissions.

✅ Public Policy & Development – Evaluate the impact of economic and environmental policies over time.

This dataset is shared for educational and analytical purposes only.

The median age indicates the age separating the population group into two halves of equal size.

About this dataset

Context

The dataset tabulates the Economy 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 Economy 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 Economy was 8,962, a 0.18% decrease year-by-year from 2022. Previously, in 2022, Economy population was 8,978, a decline of 0.74% compared to a population of 9,045 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Economy decreased by 452. In this period, the peak population was 9,414 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 Economy is shown in this column.
• Year on Year Change: This column displays the change in Economy 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 Economy Population by Year. You can refer the same here

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Wheatfield town: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 91(1.30%) households where the householder is under 25 years old, 1,745(24.97%) households with a householder aged between 25 and 44 years, 2,760(39.50%) households with a householder aged between 45 and 64 years, and 2,392(34.23%) households where the householder is over 65 years old.
• The age group of 25 to 44 years exhibits the highest median household income, while the largest number of households falls within the 45 to 64 years bracket. This distribution hints at economic disparities within the town of Wheatfield town, showcasing varying income levels among different age demographics.

Content

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

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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 Wheatfield town median household income by age. You can refer the same here

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Venice town: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 12(2.54%) households where the householder is under 25 years old, 129(27.27%) households with a householder aged between 25 and 44 years, 213(45.03%) households with a householder aged between 45 and 64 years, and 119(25.16%) households where the householder is over 65 years old.
• The age group of 25 to 44 years exhibits the highest median household income, while the largest number of households falls within the 45 to 64 years bracket. This distribution hints at economic disparities within the town of Venice town, showcasing varying income levels among different age demographics.

Content

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

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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 Venice town median household income by age. You can refer the same here

Household Current Income: % Share: CR: Quintile 4 data was reported at 21.100 % in 2015. This records a decrease from the previous number of 21.868 % for 2013. Household Current Income: % Share: CR: Quintile 4 data is updated yearly, averaging 21.400 % from Dec 2011 (Median) to 2015, with 3 observations. The data reached an all-time high of 21.868 % in 2013 and a record low of 21.100 % in 2015. Household Current Income: % Share: CR: Quintile 4 data remains active status in CEIC and is reported by National Statistical Office. The data is categorized under Global Database’s Thailand – Table TH.G042: Household Income & Assets Statistics.

BackgroundFederal policy impact analyses in the United States do not incorporate the potential economic benefits of adolescent mental health policies. Understanding the extent to which economic benefits may offset policy costs would support more effective policymaking. This study estimates the relationship between adolescent psychological distress and later health and economic outcomes and uses these estimates to determine the potential economic effects of a hypothetical policy.Methods and findingsThis analysis estimated the relationship between psychological distress in those aged 15 to 17 years in 2000 and economic and health outcomes approximately 10 years later, accounting for an array of explanatory variables using machine learning–enabled methods. The cohort was from the National Longitudinal Study of Youth 1997 and nationally representative of those aged 12 to 18 years in 1997. The cohort included 3,343 individuals under age 18 years in round 4 who completed the Mental Health Inventory-5 (MHI-5). Round 1 captured 50 explanatory variables that covered domains of potential confounders, including basic demographics, neighborhood environment, family resources, family processes, physical health, school quality, and academic skills. The exposure included a binary variable of clinically significant psychological distress (MHI-5 score of less than or equal to 3) and a categorical variable of symptom severity on the MHI-5. Outcomes covered domains of employment, income, total assets at age 30 years, education, and health approximately 10 years later.Forty-seven percent of the cohort were black and Hispanic, and 4.4% had past-month clinically significant psychological distress. Past-month clinically significant psychological distress in adolescence led to a 6-percentage-point (95% confidence interval [CI] [−0.08, −0.03]) reduction in past-year labor force participation 10 years later and $5,658 (95% CI [−6,772, −4,545]) USD fewer past-year wages earned. We used these results to model the labor market impacts of a hypothetical policy that expanded access to mental health preventive care and reached 10% of youth who would have otherwise developed clinically significant psychological distress. We found that the hypothetical policy could lead to $52 (95% credible interval [51,54]) billion USD in federal budget benefits over 10 years from labor supply impacts alone. This study faced limitations, including potential unmeasured confounding, missing data, and challenges to generalizability.ConclusionsOur findings showed the impacts of adolescent mental health policies on the federal budget and found potentially large effects on the economy if policies achieve population-level change.

Demographics

United States US: Number of Births data was reported at 4,413,478.000 Person in 2050. This records an increase from the previous number of 4,397,629.000 Person for 2049. United States US: Number of Births data is updated yearly, averaging 4,195,844.000 Person from Jun 2001 (Median) to 2050, with 50 observations. The data reached an all-time high of 4,413,478.000 Person in 2050 and a record low of 3,921,308.000 Person in 2013. United States US: Number of Births data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s United States – Table US.US Census Bureau: Demographic Projection.

United States WE: Age 25 & Over: Male: HS: Third Quartile data was reported at 1,234.000 USD in Mar 2020. This records a decrease from the previous number of 1,253.000 USD for Dec 2019. United States WE: Age 25 & Over: Male: HS: Third Quartile data is updated quarterly, averaging 1,003.000 USD from Mar 2000 (Median) to Mar 2020, with 81 observations. The data reached an all-time high of 1,253.000 USD in Dec 2019 and a record low of 793.000 USD in Mar 2000. United States WE: Age 25 & Over: Male: HS: Third Quartile data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G030: Current Population Survey: Usual Weekly Earnings.

Background: Clean water is an essential part of human healthy life and wellbeing. More recently, rapid population growth, high illiteracy rate, lack of sustainable development, and climate change; faces a global challenge in developing countries. The discontinuity of drinking water supply forces households either to use unsafe water storage materials or to use water from unsafe sources. The present study aimed to identify the determinants of water source types, use, quality of water, and sanitation perception of physical parameters among urban households in North-West Ethiopia.

Methods: A community-based cross-sectional study was conducted among households from February to March 2019. An interview-based a pretested and structured questionnaire was used to collect the data. Data collection samples were selected randomly and proportional to each of the kebeles' households. MS Excel and R Version 3.6.2 were used to enter and analyze the data; respectively. Descriptive statistics using frequencies and percentages were used to explain the sample data concerning the predictor variable. Both bivariate and multivariate logistic regressions were used to assess the association between independent and response variables.

Results: Four hundred eighteen (418) households have participated. Based on the study undertaken,78.95% of households used improved and 21.05% of households used unimproved drinking water sources. Households drinking water sources were significantly associated with the age of the participant (x2 = 20.392, df=3), educational status(x2 = 19.358, df=4), source of income (x2 = 21.777, df=3), monthly income (x2 = 13.322, df=3), availability of additional facilities (x2 = 98.144, df=7), cleanness status (x2 =42.979, df=4), scarcity of water (x2 = 5.1388, df=1) and family size (x2 = 9.934, df=2). The logistic regression analysis also indicated that those factors are significantly determining the water source types used by the households. Factors such as availability of toilet facility, household member type, and sex of the head of the household were not significantly associated with drinking water sources.

Conclusion: The uses of drinking water from improved sources were determined by different demographic, socio-economic, sanitation, and hygiene-related factors. Therefore, ; the local, regional, and national governments and other supporting organizations shall improve the accessibility and adequacy of drinking water from improved sources in the area.

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Wethersfield town: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 7(2.24%) households where the householder is under 25 years old, 89(28.43%) households with a householder aged between 25 and 44 years, 155(49.52%) households with a householder aged between 45 and 64 years, and 62(19.81%) households where the householder is over 65 years old.
• The age group of 25 to 44 years exhibits the highest median household income, while the largest number of households falls within the 45 to 64 years bracket. This distribution hints at economic disparities within the town of Wethersfield town, showcasing varying income levels among different age demographics.

Content

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

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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 Wethersfield town median household income by age. You can refer the same here

The Comprehensive Annual Financial Reports are presented in three main sections; the Introductory Section, the Financial Section, and the Statistical Section. The Introductory Section includes a financial overview, discussion of Iowa's economy and an organizational chart for State government. The Financial Section includes the state auditor's report, management's discussion and analysis, audited basic financial statements and notes thereto, and the underlying combining and individual fund financial statements and supporting schedules. The Statistical Section sets forth selected unaudited economic, financial trend and demographic information for the state on a multi-year basis. Reports for multiple fiscal years are available.

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Wenonah: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 0 households where the householder is under 25 years old, 0 households with a householder aged between 25 and 44 years, 7(87.50%) households with a householder aged between 45 and 64 years, and 1(12.50%) households where the householder is over 65 years old.
• In Wenonah, the age group of 45 to 64 years stands out with both the highest median income and the maximum share of households. This alignment suggests a financially stable demographic, indicating an established community with stable careers and higher incomes.

Content

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

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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 Wenonah median household income by age. You can refer the same here

Finland FI: Population: Male: Ages 30-34: % of Male Population data was reported at 6.656 % in 2017. This records a decrease from the previous number of 6.729 % for 2016. Finland FI: Population: Male: Ages 30-34: % of Male Population data is updated yearly, averaging 6.943 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 9.896 % in 1981 and a record low of 6.119 % in 2006. Finland FI: Population: Male: Ages 30-34: % of Male Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Finland – Table FI.World Bank: Population and Urbanization Statistics. Male population between the ages 30 to 34 as a percentage of the total male population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

Ukraine Population Distribution: with Avg Income per Capita: 3360.1 to 3720.0 UAH data was reported at 10.800 % in 2017. This records an increase from the previous number of 7.900 % for 2016. Ukraine Population Distribution: with Avg Income per Capita: 3360.1 to 3720.0 UAH data is updated yearly, averaging 3.450 % from Dec 2012 (Median) to 2017, with 6 observations. The data reached an all-time high of 10.800 % in 2017 and a record low of 2.000 % in 2013. Ukraine Population Distribution: with Avg Income per Capita: 3360.1 to 3720.0 UAH data remains active status in CEIC and is reported by State Statistics Service of Ukraine. The data is categorized under Global Database’s Ukraine – Table UA.H009: Household Income and Expenditure: Annual.

Graph and download economic data for Infra-Annual Labor Statistics: Working-Age Population Male: From 55 to 64 Years for United States (LFWA55MAUSM647S) from Jan 1977 to Aug 2025 about 55 to 64 years, working-age, males, population, and USA.

Population with Income per Capita below Living Cost: % of Total: CF: Kostroma Region data was reported at 8.000 % in 2024. This records a decrease from the previous number of 8.700 % for 2023. Population with Income per Capita below Living Cost: % of Total: CF: Kostroma Region data is updated yearly, averaging 17.350 % from Dec 1995 (Median) to 2024, with 30 observations. The data reached an all-time high of 38.300 % in 1999 and a record low of 8.000 % in 2024. Population with Income per Capita below Living Cost: % of Total: CF: Kostroma Region data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Demographic and Labour Market – Table RU.GA015: Population with Income per Capita below Living Cost.