This data package includes the underlying data files to replicate the data and charts presented in The Inflation Surge in Europe by Patrick Honohan, PIIE Policy Brief 24-2.

If you use the data, please cite as: Honohan, Patrick. 2024. The Inflation Surge in Europe. PIIE Policy Brief 24-2. Washington, DC: Peterson Institute for International Economics.

Inflation Rate in Pakistan decreased to 3.20 percent in June from 3.50 percent in May of 2025. This dataset provides the latest reported value for - Pakistan Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Abstract of associated article: Increasing the independence of a central bank from political influence, although ex-ante socially beneficial and initially successful in reducing inflation, would ultimately fail to lower inflation permanently. The smaller anticipated policy distortions implemented by a more independent central bank would induce the fiscal authority to decrease current distortions by increasing the deficit. Over time, inflation would increase to accommodate a higher public debt. By contrast, imposing a strict inflation target would lower inflation permanently and insulate the primary deficit from political distortions.

This submission includes publicly available data extracted in its original form. Please reference the Related Publication listed here for source and citation information "The Environmental and Climate Justice Program (ECJ Program), created by the Inflation Reduction Act (IRA), provides funding for financial and technical assistance to carry out environmental and climate justice activities to benefit disadvantaged communities. EPA has created the EPA Disadvantaged Community Environmental and Climate Justice Program map to assist potential applicants seeking to identify whether a community is disadvantaged for the purposes of implementing the ECJ Program. The EPA Disadvantaged Communities Environmental and Climate Justice program map includes the following components: EPA IRA Disadvantaged Communities 1.0 map EPA IRA Disadvantaged Communities 2.0 map Any area of American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, or the U.S. Virgin Islands The EPA IRA Disadvantaged Communities maps combines multiple datasets that individually can be used to determine whether a community is disadvantaged for the purposes of implementing programs under the IRA. All data sets are assigned values at the Census block group level. The criteria and associated datasets used in the maps are: Any census tract that is included as disadvantaged in the Climate and Economic Justice Screening Tool (CEJST) Any census block group at or above the 90th percentile for any of EJScreen’s Supplemental Indexes when compared to the nation or state, and/or any of the following geographic areas within the Tribal lands category in EJScreen: Alaska Native Allotments Alaska Native Villages American Indian Reservations American Indian Off-reservation Trust Lands Oklahoma Tribal Statistical Areas The EPA IRA Disadvantaged Communities 1.0 map uses data from EJScreen version 2.2. The EPA IRA Disadvantaged Communities 2.0 map uses data from EJScreen version 2.3. To further assist applicants, EPA has provided the underlying data for the map" [Quote from https://www.epa.gov/environmentaljustice/inflation-reduction-act-disadvantaged-communities-map] Note: If you have questions about the underlying data, please contact the Environmental Protection Agency (environmental-justice@epa.gov). If you have questions or recommendations related to this metadata entry, please contact the CAFE Data Management team at: climatecafe@bu.edu

On November 15, 2021, President Biden signed the Bipartisan Infrastructure Law (BIL), which invests more than $13 billion directly in Tribal communities across the country and makes Tribal communities eligible for billions more. For further explanation of the law please visit https://www.congress.gov/bill/117th-congress/house-bill/3684/text. These resources go to many Federal agencies to expand access to clean drinking water for Native communities, ensure every Native American has access to high-speed internet, tackle the climate crisis, advance environmental justice, and invest in Tribal communities that have too often been left behind. On August 16, 2022, President Biden signed the Inflation Reduction Act into law, marking the most significant action Congress has taken on clean energy and climate change in the nation’s history. With the stroke of his pen, the President redefined American leadership in confronting the existential threat of the climate crisis and set forth a new era of American innovation and ingenuity to lower consumer costs and drive the global clean energy economy forward. More information on this can be found here: https://www.whitehouse.gov/cleanenergy/inflation-reduction-act-guidebook/. This dataset illustrates the locations of Bureau of Indian Affairs projects funded by the Bipartisan Infrastructure Law and Inflation Reduction Act in Fiscal Year 2022, 2023, and 2024. The points illustrated in this dataset are the locations of Bureau of Indian Affairs projects funded by the Bipartisan Infrastructure Law and Inflation Reduction Act in Fiscal Year 2022 and 2023. The locations for the points in this layer were provided by the persons involved in the following groups: Division of Water and Power, DWP, Ecosystem Restoration, Irrigation, Power, Water Sanitation, Dam Safety, Branch of Geospatial Support, Bureau of Indian Affairs, BIA.GIS point feature class was created by Bureau of Indian Affairs - Branch Of Geospatial Support (BOGS), Division of Water and Power (DWP), Ecosystem Restoration, Irrigation, Bureau of Indian Affairs (BIA), Tribal Leaders Directory: https://www.bia.gov/service/tribal-leaders-directory/tld-csvexcel-dataset, The Department of the Interior | Strategic Hazard Identification and Risk Assessment Project: https://www.doi.gov/emergency/shira#main-content

About this dataset

Context

The dataset illustrates the median household income in Cut Bank, spanning the years from 2010 to 2023, with all figures adjusted to 2023 inflation-adjusted dollars. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

Key observations:

From 2010 to 2023, the median household income for Cut Bank decreased by $1,749 (3.04%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $5,602 (7.68%) between 2010 and 2023.

Analyzing the trend in median household income between the years 2010 and 2023, spanning 13 annual cycles, we observed that median household income, when adjusted for 2023 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 7 years and declined for 6 years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Years for which data is available:

• 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 0223

Variables / Data Columns

• Year: This column presents the data year from 2010 to 2023
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific year
• YOY Change($): Change in median household income between the current and the previous year, in 2023 inflation-adjusted dollars
• YOY Change(%): Percent change in median household income between current and the previous year

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 Cut Bank median household income. You can refer the same here

On November 15, 2021, President Biden signed the Bipartisan Infrastructure Law (BIL), which invests more than $13 billion directly in Tribal communities across the country and makes Tribal communities eligible for billions more. For further explanation of the law please visit https://www.congress.gov/bill/117th-congress/house-bill/3684/text. These resources go to many Federal agencies to expand access to clean drinking water for Native communities, ensure every Native American has access to high-speed internet, tackle the climate crisis, advance environmental justice, and invest in Tribal communities that have too often been left behind. On August 16, 2022, President Biden signed the Inflation Reduction Act into law, marking the most significant action Congress has taken on clean energy and climate change in the nation’s history. With the stroke of his pen, the President redefined American leadership in confronting the existential threat of the climate crisis and set forth a new era of American innovation and ingenuity to lower consumer costs and drive the global clean energy economy forward. More information on this can be found here: https://www.whitehouse.gov/cleanenergy/inflation-reduction-act-guidebook/ .This dataset illustrates the locations of Bureau of Indian Affairs projects funded by the Bipartisan Infrastructure Law and Inflation Reduction Act in Fiscal Year 2022 and 2023.The points illustrated in this dataset are the locations of Bureau of Indian Affairs projects funded by the Bipartisan Infrastructure Law and Inflation Reduction Act in Fiscal Year 2022 and 2023. The locations for the points in this layer were provided by the persons involved in the following groups: Division of Water and Power, DWP, Ecosystem Restoration, Irrigation, Power, Water Sanitation, Dam Safety, Branch of Geospatial Support, Bureau of Indian Affairs, BIA. GIS point feature class was created by Bureau of Indian Affairs - Branch Of Geospatial Support (BOGS), Division of Water and Power (DWP), Ecosystem Restoration, Irrigation, Bureau of Indian Affairs (BIA), Tribal Leaders Directory: https://www.bia.gov/service/tribal-leaders-directory/tld-csvexcel-dataset, The Department of the Interior | Strategic Hazard Identification and Risk Assessment Project: https://www.doi.gov/emergency/shira#main-content Please feel free to contact BOGS at 1-877-293-9494 geospatial@bia.gov

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Cut Bank. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Cut Bank. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2023

In terms of income distribution across age cohorts, in Cut Bank, householders within the 45 to 64 years age group have the highest median household income at $65,417, followed by those in the 25 to 44 years age group with an income of $57,865. Meanwhile householders within the under 25 years age group report the second lowest median household income of $40,703. Notably, householders within the 65 years and over age group, had the lowest median household income at $32,500.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific age group

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

This data package includes the underlying data files to replicate the data, tables, and charts presented in How the United States solved South Korea’s problems with electric vehicle subsidies under the Inflation Reduction Act, PIIE Working Paper 23-6.

If you use the data, please cite as: Bown, Chad P. 2023. How the United States solved South Korea’s problems with electric vehicle subsidies under the Inflation Reduction Act. PIIE Working Paper 23-6. Washington, DC: Peterson Institute for International Economics.

About this dataset

Context

The dataset tabulates the Cut Bank household income by gender. The dataset can be utilized to understand the gender-based income distribution of Cut Bank 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).

• Cut Bank, MT annual median income by work experience and sex dataset : Aged 15+, 2010-2022 (in 2022 inflation-adjusted dollars)
• Cut Bank, MT annual income distribution by work experience and gender dataset (Number of individuals ages 15+ with income, 2021)

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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Cut Bank income distribution by gender. You can refer the same here

About this dataset

Context

The dataset illustrates the median household income in Cut And Shoot, spanning the years from 2010 to 2023, with all figures adjusted to 2023 inflation-adjusted dollars. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

Key observations:

From 2010 to 2023, the median household income for Cut And Shoot increased by $11,687 (19.96%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $5,602 (7.68%) between 2010 and 2023.

Analyzing the trend in median household income between the years 2010 and 2023, spanning 13 annual cycles, we observed that median household income, when adjusted for 2023 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 6 years and declined for 7 years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Years for which data is available:

• 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 0223

Variables / Data Columns

• Year: This column presents the data year from 2010 to 2023
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific year
• YOY Change($): Change in median household income between the current and the previous year, in 2023 inflation-adjusted dollars
• YOY Change(%): Percent change in median household income between current and the previous year

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 Cut And Shoot median household income. You can refer the same here

This table shows inflation, derived inflation and underlying inflation rates. Underlying inflation equals the inflation or derived inflation, excluding certain volatile items or series that are affected by factors other than general economic conditions, for example prices of fuel, vegetables, fruit and government taxes.

Data available from: January 2006 till December 2015

Status of the figures: The figures in this table are final.

Changes as of 16 June 2016: None, this table is stopped.

Changes as of 10 December 2015: On 1 October 2015, the points system for the pricing of rental homes was adjusted by the Dutch national government. As a direct consequence, rental prices of a limited number of dwellings were reduced, which had a downward effect on the average rental price. The effect of this decrease on the rental price indices and imputed rent value could not be determined in time because housing associations announced the impact of rent adjustments only in November. For this reason, the figures of the groups 04100 ‘Actual rentals for housing’ and 04200 ‘Imputed rent value’ over October 2015 have now been adjusted.

The figures of the groups 061100 ‘Pharmaceutical products’, 061200 ‘Other medical products, equipment’, 072200 ‘Fuels and lubricants’ and 083000 ‘Telephone and internet services’ over the months June through September 2015 have been corrected. This has no impact on the headline indices.

The derived CPI decreased by 0.01 index point over August 2015.

About this dataset

Context

The dataset presents the median household income across different racial categories in Cut Bank. 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 Cut Bank population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 69.97% of the total residents in Cut Bank. Notably, the median household income for White households is $65,060. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $65,060.

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 Cut Bank.
• 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 Cut Bank median household income by race. You can refer the same here

Nigeria’s inflation has been higher than the average for African and Sub-Saharan countries for years now, and even exceeded 16 percent in 2017 – and a real, significant decrease is nowhere in sight. The bigger problem is its unsteadiness, however: An inflation rate that is bouncing all over the place, like this one, is usually a sign of a struggling economy, causing prices to fluctuate, and unemployment and poverty to increase. Nigeria’s economy - a so-called “mixed economy”, which means the market economy is at least in part regulated by the state – is not entirely in bad shape, though. More than half of its GDP is generated by the services sector, namely telecommunications and finances, and the country derives a significant share of its state revenues from oil.

Because it got high

To simplify: When the inflation rate rises, so do prices, and consequently banks raise their interest rates as well to cope and maintain their profit margin. Higher interest rates often cause unemployment to rise. In certain scenarios, rising prices can also mean more panicky spending and consumption among end users, causing debt and poverty. The extreme version of this is called hyperinflation: A rapid increase of prices that is out of control and leads to bankruptcies en masse, devaluation of money and subsequently a currency reform, among other things. But does that mean that low inflation is better? Maybe, but only to a certain degree; the ECB, for example, aspires to maintain an inflation rate of about two percent so as to keep the economy stable. As soon as we reach deflation territory, however, things are starting to look grim again. The best course is a stable inflation rate, to avoid uncertainty and rash actions.

Nigeria today

Nigeria is one of the countries with the largest populations worldwide and also the largest economy in Africa, with its economy growing rapidly after a slump in the aforementioned year 2017. It is slated to be one of the countries with the highest economic growth over the next few decades. Demographic key indicators, like infant mortality rate, fertility rate, and the median age of the population, all point towards a bright future. Additionally, the country seems to make big leaps forward in manufacturing and technological developments, and boasts huge natural resources, including natural gas. All in all, Nigeria and its inflation seem to be on the upswing – or on the path to stabilization, as it were.

Inflation Rate in Nigeria decreased to 22.97 percent in May from 23.71 percent in April of 2025. This dataset provides - Nigeria Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This data package includes the underlying data files to replicate the data and charts presented in Industrial policy for electric vehicle supply chains and the US-EU fight over the Inflation Reduction Act, PIIE Working Paper 23-1.

If you use the data, please cite as: Bown, Chad P. (2023). Industrial policy for electric vehicle supply chains and the US-EU fight over the Inflation Reduction Act, PIIE Working Paper 23-1. Peterson Institute for International Economics.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Cut Bank. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Cut Bank, the median income for all workers aged 15 years and older, regardless of work hours, was $40,338 for males and $20,603 for females.

These income figures highlight a substantial gender-based income gap in Cut Bank. Women, regardless of work hours, earn 51 cents for each dollar earned by men. This significant gender pay gap, approximately 49%, underscores concerning gender-based income inequality in the city of Cut Bank.

- Full-time workers, aged 15 years and older: In Cut Bank, among full-time, year-round workers aged 15 years and older, males earned a median income of $49,265, while females earned $50,000

Surprisingly, within the subset of full-time workers, women earn a higher income than men, earning 1.01 dollars for every dollar earned by men. This suggests that within full-time roles, womens median incomes significantly surpass mens, contrary to broader workforce trends.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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 Cut Bank median household income by race. You can refer the same here

About this dataset

Context

The dataset tabulates the Cut And Shoot household income by gender. The dataset can be utilized to understand the gender-based income distribution of Cut And Shoot 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).

• Cut And Shoot, TX annual median income by work experience and sex dataset : Aged 15+, 2010-2022 (in 2022 inflation-adjusted dollars)
• Cut And Shoot, TX annual income distribution by work experience and gender dataset (Number of individuals ages 15+ with income, 2021)

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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Cut And Shoot income distribution by gender. You can refer the same here

About this dataset

Context

The dataset presents median household incomes for various household sizes in Cut Bank, MT, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, Cut Bank did not include 4, 5, 6, or 7-person households. Across the different household sizes in Cut Bank the mean income is $55,962, and the standard deviation is $18,676. The coefficient of variation (CV) is 33.37%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $39,006. It then further increased to $52,902 for 3-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/cut-bank-mt-median-household-income-by-household-size.jpeg" alt="Cut Bank, MT median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

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

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

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 Cut Bank median household income. You can refer the same here

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Cut And Shoot. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Cut And Shoot, the median income for all workers aged 15 years and older, regardless of work hours, was $42,153 for males and $28,313 for females.

These income figures highlight a substantial gender-based income gap in Cut And Shoot. Women, regardless of work hours, earn 67 cents for each dollar earned by men. This significant gender pay gap, approximately 33%, underscores concerning gender-based income inequality in the city of Cut And Shoot.

- Full-time workers, aged 15 years and older: In Cut And Shoot, among full-time, year-round workers aged 15 years and older, males earned a median income of $76,250, while females earned $38,942, leading to a 49% gender pay gap among full-time workers. This illustrates that women earn 51 cents for each dollar earned by men in full-time roles. This level of income gap emphasizes the urgency to address and rectify this ongoing disparity, where women, despite working full-time, face a more significant wage discrepancy compared to men in the same employment roles.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Cut And Shoot, showcasing a consistent income pattern irrespective of employment status.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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 Cut And Shoot median household income by race. You can refer the same here