This statistic illustrates the share of people owning a Ford in the United States. As of **************, ** percent of 18 - 29 year old consumers do so in the U.S. This is according to exclusive results from the Consumer Insights Global survey which shows that ** percent of 30 - 49 year old customers also fall into this category.Statista Consumer Insights offer you all results of our exclusive Statista surveys, based on more than ********* interviews.

At about *** million units, the U.S. is the number one sales market for the Ford Motor Company. Globally, sales grew by about ****** units between 2023 and 2024. Slow sales in international markets China is Ford's second-largest market, despite reporting lower sales in 2024. Ford may have been worried about this market, as the United States and China were on the brink of an economic conflict. Tensions remain high as President Biden continues his term in office. The two nations are among the three largest economies in the world. With them is the European Union. There, Ford sales are also under threat. The UK's withdrawal from the European Union disrupts Fords supply chains: three plants operate in the UK, which has now been cut off from assembly locations in the EU. The UK was traditionally Ford's largest market in Europe. Wholesales in the UK came to around ******* units in 2024, and dealerships recorded lower monthly sales of Ford vehicles to end customers in the United Kingdom of Great Britain and Northern Ireland in 2024 when compared to 2019. However, the Ford Puma was the best-selling model in the UK in 2024. Declining domestic market share The Ford Motor Company is among the leading manufacturers in its domestic market, surpassed only by the General Motors Company and Toyota Motor Corporation. This success in the United States' market can be mostly attributed to the manufacturer's eponymous brand, Ford, which was the best-selling brand in the country that year. Its F-Series pickup truck was also among the bestsellers of that type, giving Ford a competitive advantage in its domestic market as light trucks, including pickups, were more popular with consumers than passenger cars.

Ford’s research and development (R&D) expenditures came to about eight billion U.S. dollars in 2024. The Michigan-based company appears to be adapting to altered fuel economy regulations and the declining demand for sedans and smaller cars in the United States by developing new designs and products. Focus of research and development activities In light of an increased concern from consumers and policymakers about the impact of fossil fuels on carbon dioxide emissions, Ford is working on a new fleet of electric vehicles with a goal for 40 or 50 percent of its global vehicle volume to be fully electric by 2030. In June 2020, it was announced that Ford will gain access to Volkswagen's modular electric drive (MEB) architecture to assemble electric vehicles (EVs), a partnership which was expanded in March 2022 as Ford planned to produce another electric model for the European market based on Volkswagen's MEB platform. This move put a halt to a planned partnership between Ford's Lincoln brand and EV startup Rivian to build EVs. In 2022, Ford sold around 91 million shares in Rivian. In September 2021, the manufacturer further announced plans to open campuses in Tennessee and Kentucky to build the next generation of electric F-series trucks and batteries. The F-Series was among the best-selling cars and light trucks worldwide.Another focus of Ford’s research and development department is artificial intelligence (AI). For example, Ford has invested more than one billion U.S. dollars in Argo AI, the most well-funded U.S.-based AI startup. Ford used Argo AI technology in its vehicles; partially autonomous cars are expected to become a large market by 2025.

In 2024, Ford remained the leading car brand in the United States based on vehicle sales, delivering about *** million units to U.S. customers. The United States is the largest market for Ford: wholesales to U.S. dealerships reached over *** million vehicles in 2023. Car sales among major manufacturers The top three U.S. car brands are assembled and distributed by the leading manufacturers in the U.S. market: Ford Motor Company, Toyota Motor Corporation, and General Motors (GM). As of the fourth quarter of 2024, GM's largest segment of sales was attributable to its Chevrolet-badged vehicles. Within the Ford Motor Corporation, the Ford division accounted for the largest number of vehicle sales. And finally, Toyota’s largest distribution of this sales volume was attributable to the Toyota brand vehicles. Automotive industry overview Production and sales volumes are declining among the key automotive brands in the United States, as a result of the accelerated automotive semiconductor shortage, the COVID-19 pandemic, and the fact that the automotive manufacturing and sales market is highly competitive both within the U.S. and globally. Electric vehicles emerged as the leading trend in Europe since 2020 and the U.S. electric vehicle industry has been catching up. Furthermore, it is forecast that autonomous vehicles will disrupt the U.S. market between 2020 and 2030.

The global passenger vehicle market is experiencing robust growth, driven by several key factors. The increasing global population, particularly in developing economies, fuels demand for personal transportation. Rising disposable incomes and improved infrastructure in these regions further contribute to market expansion. Technological advancements, such as the development of electric vehicles (EVs), hybrid vehicles, and advanced driver-assistance systems (ADAS), are reshaping the industry landscape, attracting a broader customer base and increasing the average vehicle price. While supply chain disruptions and the fluctuating price of raw materials pose challenges, the overall market outlook remains positive, fueled by government incentives for environmentally friendly vehicles and a growing preference for safer and more technologically advanced cars. We estimate the market size in 2025 to be around $2.5 trillion, based on industry reports and considering the historical growth trends and projected CAGR. This figure is expected to see continued growth through 2033, with a compounded annual growth rate (CAGR) in the range of 5-7% annually. Major players such as Ford, General Motors, Honda, Hyundai, Toyota, and Volkswagen are actively competing to capture market share through innovation and expansion into emerging markets. Competition is fierce, leading to continuous product development, enhanced features, and competitive pricing strategies. However, regulatory pressures related to emissions standards and safety regulations are also significant factors impacting manufacturers' strategies. Regional variations exist, with North America and Asia-Pacific expected to remain dominant markets due to their large populations and robust automotive industries. Nevertheless, Europe and other regions are witnessing increasing demand driven by urbanization and infrastructure development. The long-term growth trajectory depends on several factors, including economic stability, technological breakthroughs, and government policies. The shift toward sustainability, with increased adoption of electric and hybrid vehicles, is a key driver expected to transform the market over the forecast period.

Ford Campus Vision and Lidar Data Set is a dataset collected by an autonomous ground vehicle testbed, based upon a modified Ford F-250 pickup truck. The vehicle is outfitted with a professional (Applanix POS LV) and consumer (Xsens MTI-G) Inertial Measuring Unit (IMU), a Velodyne 3D-lidar scanner, two push-broom forward looking Riegl lidars, and a Point Grey Ladybug3 omnidirectional camera system.

This dataset consists of the time-registered data from these sensors mounted on the vehicle, collected while driving the vehicle around the Ford Research campus and downtown Dearborn, Michigan during November-December 2009. The vehicle path trajectory in these datasets contain several large and small-scale loop closures, which should be useful for testing various state of the art computer vision and SLAM (Simultaneous Localization and Mapping) algorithms.

Paper: Ford Campus vision and lidar data set

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Ford County. 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 Ford County. 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 Ford County, householders within the 45 to 64 years age group have the highest median household income at $90,513, followed by those in the 25 to 44 years age group with an income of $75,968. Meanwhile householders within the under 25 years age group report the second lowest median household income of $47,097. Notably, householders within the 65 years and over age group, had the lowest median household income at $43,962.

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

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Address Ranges Relationship File (ADDR.dbf) contains the attributes of each address range. Each address range applies to a single edge and has a unique address range identifier (ARID) value. The edge to which an address range applies can be determined by linking the address range to the All Lines Shapefile (EDGES.shp) using the permanent topological edge identifier (TLID) attribute. Multiple address ranges can apply to the same edge since an edge can have multiple address ranges. Note that the most inclusive address range associated with each side of a street edge already appears in the All Lines Shapefile (EDGES.shp). The TIGER/Line Files contain potential address ranges, not individual addresses. The term "address range" refers to the collection of all possible structure numbers from the first structure number to the last structure number and all numbers of a specified parity in between along an edge side relative to the direction in which the edge is coded. The address ranges in the TIGER/Line Files are potential ranges that include the full range of possible structure numbers even though the actual structures may not exist.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Address Ranges Relationship File (ADDR.dbf) contains the attributes of each address range. Each address range applies to a single edge and has a unique address range identifier (ARID) value. The edge to which an address range applies can be determined by linking the address range to the All Lines Shapefile (EDGES.shp) using the permanent topological edge identifier (TLID) attribute. Multiple address ranges can apply to the same edge since an edge can have multiple address ranges. Note that the most inclusive address range associated with each side of a street edge already appears in the All Lines Shapefile (EDGES.shp). The TIGER/Line Files contain potential address ranges, not individual addresses. The term "address range" refers to the collection of all possible structure numbers from the first structure number to the last structure number and all numbers of a specified parity in between along an edge side relative to the direction in which the edge is coded. The address ranges in the TIGER/Line Files are potential ranges that include the full range of possible structure numbers even though the actual structures may not exist.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Edge refers to the linear topological primitives that make up MTDB. The All Lines Shapefile contains linear features such as roads, railroads, and hydrography. Additional attribute data associated with the linear features found in the All Lines Shapefile are available in relationship (.dbf) files that users must download separately. The All Lines Shapefile contains the geometry and attributes of each topological primitive edge. Each edge has a unique TIGER/Line identifier (TLID) value.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The All Roads Shapefile includes all features within the MTDB Super Class "Road/Path Features" distinguished where the MAF/TIGER Feature Classification Code (MTFCC) for the feature in MTDB that begins with "S". This includes all primary, secondary, local neighborhood, and rural roads, city streets, vehicular trails (4wd), ramps, service drives, alleys, parking lot roads, private roads for service vehicles (logging, oil fields, ranches, etc.), bike paths or trails, bridle/horse paths, walkways/pedestrian trails, and stairways.

About this dataset

Context

The dataset presents the median household income across different racial categories in Ford City. 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 Ford City population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 98.02% of the total residents in Ford City. Notably, the median household income for White households is $56,825. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $56,825.

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 Ford City.
• 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 Ford City median household income by race. 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 Ford town. 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 Ford town, the median income for all workers aged 15 years and older, regardless of work hours, was $75,431 for males and $17,500 for females.

These income figures highlight a substantial gender-based income gap in Ford town. Women, regardless of work hours, earn 23 cents for each dollar earned by men. This significant gender pay gap, approximately 77%, underscores concerning gender-based income inequality in the town of Ford town.

- Full-time workers, aged 15 years and older: In Ford town, among full-time, year-round workers aged 15 years and older, males earned a median income of $77,083, while females earned $26,989, leading to a 65% gender pay gap among full-time workers. This illustrates that women earn 35 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 Ford town, 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 Ford town median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Ford town. Based on the latest 2017-2021 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Ford town. 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 2021

In terms of income distribution across age cohorts, in Ford town, the median household income stands at $211,089 for householders within the 45 to 64 years age group, followed by $117,549 for the 25 to 44 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $35,130.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-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 2022 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 Ford town median household income by age. You can refer the same here

At around **** percent, General Motors held the largest share of the auto market in the United States in 2024. General Motors remained the most successful automotive manufacturer in the United States. Between 2004 and 2021, however, the manufacturer lost market share, while that of Toyota rose as a result of an increased focus on light truck models in the lineup. This shifted in 2022, but 2023 led to another slight drop in market share of the American automaker. Asian manufacturers dominate non-domestic competition Among the non-domestic manufacturers, Asian automakers proved to be the most successful group. Asian car brands selling vehicles to customers in the United States include Toyota, Honda, Nissan, Hyundai, and Subaru. Toyota was also among the most valuable automotive brands worldwide as of June 2024. Both Toyota and Lexus were among the ten brands with the highest consumer satisfaction in the United States that same year. How many brands do auto manufacturers own? General Motors, Ford, and Toyota are the leading automotive manufacturers based on market share in the United States. The Ford Motor Company mainly sells vehicles under its namesake brand, while the Toyota Motor Corporation offers several brands, including Lexus and Toyota. General Motors sells vehicles under various brands, including Chevrolet, Buick, and GMC. In 2017, GM and PSA Group closed a deal in which the French carmaker acquired GM's Opel and Vauxhall brands.

About this dataset

Context

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

• Ford County, IL annual median income by work experience and sex dataset : Aged 15+, 2010-2022 (in 2022 inflation-adjusted dollars)
• Ford County, IL 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 Ford County income distribution by gender. You can refer the same here

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Ford, Wisconsin, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Ford, Wisconsin reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Ford town households based on income levels.

Key observations

• For Family Households: In Ford town, the majority of family households, representing 42.71%, earn $200,000 or more, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.0%, have incomes falling $25,000 to $29,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Ford town, the majority of non-family households, accounting for 26.83%, have income $60,000 to $74,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.0%, earn $25,000 to $29,999, representing a smaller, yet notable, portion of non-family households in the community.

Content

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

Income Levels:

• 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
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Ford, Wisconsin (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Ford, Wisconsin
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Ford, Wisconsin
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Ford, Wisconsin

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 Ford town median household income. You can refer the same here

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Rocky Ford. 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 Rocky Ford. 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 Rocky Ford, householders within the 45 to 64 years age group have the highest median household income at $59,676, followed by those in the under 25 years age group with an income of $48,266. Meanwhile householders within the 25 to 44 years age group report the second lowest median household income of $32,839. Notably, householders within the 65 years and over age group, had the lowest median household income at $30,192.

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

About this dataset

Context

The dataset tabulates the Ford household income by age. The dataset can be utilized to understand the age-based income distribution of Ford 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).

• Ford, KS annual median income by age groups dataset (in 2022 inflation-adjusted dollars)
• Age-wise distribution of Ford, KS household incomes: Comparative analysis across 16 income brackets

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 Ford income distribution by age. You can refer the same here

About this dataset

Context

The dataset tabulates the Ford town household income by age. The dataset can be utilized to understand the age-based income distribution of Ford town 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).

• Ford, Wisconsin annual median income by age groups dataset (in 2022 inflation-adjusted dollars)
• Age-wise distribution of Ford, Wisconsin household incomes: Comparative analysis across 16 income brackets

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

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Explore our comprehensive data analysis and visual representations for a deeper understanding of Ford town income distribution by age. You can refer the same here