In 2023, the average annual pay of employees in Georgia totaled to 68,612 U.S. dollars. This is both an increase from the previous year, and from 2001 levels, when this figure stood at 35,136 U.S. dollars.

In 2023, the median household income in Georgia amounted to 72,420 U.S. dollars. This is an increase from the previous year, when the median household income in the state was 67,730 U.S. dollars. Data for the median household income in the United States as a whole may be accessed here.

Georgia Monthly Average Gross Salary: Annual data was reported at 999.134 GEL in 2017. This records an increase from the previous number of 940.010 GEL for 2016. Georgia Monthly Average Gross Salary: Annual data is updated yearly, averaging 277.872 GEL from Dec 1995 (Median) to 2017, with 23 observations. The data reached an all-time high of 999.134 GEL in 2017 and a record low of 13.500 GEL in 1995. Georgia Monthly Average Gross Salary: Annual data remains active status in CEIC and is reported by National Statistics Office of Georgia. The data is categorized under Global Database’s Georgia – Table GE.G010: Monthly Average Gross Salary.

Wages in Manufacturing in the United States increased to 28.64 USD/Hour in February from 28.54 USD/Hour in January of 2025. This dataset provides - United States Average Hourly Wages in Manufacturing - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Graph and download economic data for Laborers' Average Hourly Rate of Wages, Weighted for United States (A08139USA052NNBR) from 1860 to 1891 about hours, wages, labor, rate, and USA.

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Georgia, Vermont, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 24,664, while the mean income for the highest quintile (20% of households with the highest income) is 237,813. This indicates that the top earners earn 10 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 389,400, which is 163.74% higher compared to the highest quintile, and 1578.82% higher compared to the lowest quintile.

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:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

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

Georgia Monthly Average Gross Salary: Annual: NACE 1.1: Transport and Communications data was reported at 1,288.857 GEL in 2017. This records an increase from the previous number of 1,201.528 GEL for 2016. Georgia Monthly Average Gross Salary: Annual: NACE 1.1: Transport and Communications data is updated yearly, averaging 579.975 GEL from Dec 1998 (Median) to 2017, with 20 observations. The data reached an all-time high of 1,288.857 GEL in 2017 and a record low of 77.600 GEL in 1998. Georgia Monthly Average Gross Salary: Annual: NACE 1.1: Transport and Communications data remains active status in CEIC and is reported by National Statistics Office of Georgia. The data is categorized under Global Database’s Georgia – Table GE.G010: Monthly Average Gross Salary.

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 Georgia. 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 Georgia, the median income for all workers aged 15 years and older, regardless of work hours, was $45,231 for males and $31,459 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 30% between the median incomes of males and females in Georgia. With women, regardless of work hours, earning 70 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thestate of Georgia.

- Full-time workers, aged 15 years and older: In Georgia, among full-time, year-round workers aged 15 years and older, males earned a median income of $62,301, while females earned $50,919, leading to a 18% gender pay gap among full-time workers. This illustrates that women earn 82 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same 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 Georgia, 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 Georgia median household income by race. You can refer the same here

This graph shows average wages around the world in 2012 as calculated by purchasing power parity. In 2012 the highest average wage was earned in Luxembourg at 4,089 purchasing power parity dollars. Wages and salaries Wages and salaries in the United States have increased during the last decades. The median weekly earnings of a full-time wage and salary worker were about 241 U.S. dollars in 1979 and shifted up to 768 U.S. dollars in 2012.

The median earnings of U.S. full-time wage and salary workers vary across their educational attainment. The highest paid workers are those who hold a bachelor’s degree, according to the U.S. Bureau of Labor Statistics.

The U.S. federal government specified minimum wage laws for workers in the United States, which say that workers must be paid no less than the current federal minimum wage. The minimum wage was set at 7.25 U.S. dollars per hour by federal law. The actual minimum wage varies from state to state, as some states have additional minimum wage laws.

For instance, the minimum wage in Washington was around 9.04 U.S. dollars per hour, while the worst minimum wage can be found in Georgia, where workers earn at least 5.15 U.S. dollars per hour. No minimum wages can be found in Tennessee, Alabama, Louisiana, South Carolina and Mississippi, as of January 1, 2012.

The number of workers paid hourly rates with earnings at or below the minimum wage in the U.S. was at its highest in the industry type of leisure and hospitality in 2013.

Recent statistics show that the share of female workers paid hourly rates at or below prevailing federal minimum wage in the United States decreased since 1979. In that year, 20.2 percent of the female wage and salary workers were paid below the federal minimum wage, while only 2.9 percent of the female workers were paid below the federal minimum wage in 2006.

Georgia Monthly Average Gross Salary: Annual: NACE 1.1: Health Care and Social Services data was reported at 953.121 GEL in 2017. This records an increase from the previous number of 914.389 GEL for 2016. Georgia Monthly Average Gross Salary: Annual: NACE 1.1: Health Care and Social Services data is updated yearly, averaging 256.069 GEL from Dec 1998 (Median) to 2017, with 20 observations. The data reached an all-time high of 953.121 GEL in 2017 and a record low of 25.700 GEL in 1998. Georgia Monthly Average Gross Salary: Annual: NACE 1.1: Health Care and Social Services data remains active status in CEIC and is reported by National Statistics Office of Georgia. The data is categorized under Global Database’s Georgia – Table GE.G010: Monthly Average Gross Salary.

This layer shows median household income by race and by age of householder. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Median income and income source is based on income in past 12 months of survey. This layer is symbolized to show median household income. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B19013B, B19013C, B19013D, B19013E, B19013F, B19013G, B19013H, B19013I, B19049, B19053Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Georgia Monthly Average Gross Salary: Female: NACE 2: Other Service Activities data was reported at 637.187 GEL in Mar 2018. This records a decrease from the previous number of 737.666 GEL for Dec 2017. Georgia Monthly Average Gross Salary: Female: NACE 2: Other Service Activities data is updated quarterly, averaging 625.046 GEL from Mar 2014 (Median) to Mar 2018, with 17 observations. The data reached an all-time high of 1,047.071 GEL in Dec 2015 and a record low of 422.145 GEL in Mar 2014. Georgia Monthly Average Gross Salary: Female: NACE 2: Other Service Activities data remains active status in CEIC and is reported by National Statistics Office of Georgia. The data is categorized under Global Database’s Georgia – Table GE.G010: Monthly Average Gross Salary.

About this dataset

Context

The dataset illustrates the median household income in Varnell, 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 Varnell increased by $26,756 (47.69%), 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 8 years and declined for 5 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 Varnell median household income. You can refer the same here

Graph and download economic data for Estimate of Median Household Income for Taliaferro County, GA (MHIGA13265A052NCEN) from 1989 to 2023 about Taliaferro County, GA; GA; households; median; income; and USA.

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 Georgia 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 Georgia town, the median income for all workers aged 15 years and older, regardless of work hours, was $51,157 for males and $51,741 for females.

Contrary to expectations, women in Georgia town, women, regardless of work hours, earn a higher income than men, earning 1.01 dollars for every dollar earned by men. This analysis indicates a significant shift in income dynamics favoring females.

- Full-time workers, aged 15 years and older: In Georgia town, among full-time, year-round workers aged 15 years and older, males earned a median income of $70,981, while females earned $68,798, resulting in a 3% gender pay gap among full-time workers. This illustrates that women earn 97 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the town of Georgia town.

Surprisingly, across all roles (including non-full-time employment), women had a higher median income compared to men in Georgia town. This might indicate a more favorable income scenario for female workers across different employment patterns within the town of Georgia town, especially in non-full-time positions.

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 Georgia town median household income by race. You can refer the same here

Graph and download economic data for Average Weekly Wages for Employees in Private Establishments in Savannah, GA (MSA) (ENUC423440510SA) from Q1 1990 to Q2 2021 about Savannah, establishments, GA, average, wages, private, employment, and USA.

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Winder: 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 73(1.03%) households where the householder is under 25 years old, 3,000(42.16%) households with a householder aged between 25 and 44 years, 2,385(33.52%) households with a householder aged between 45 and 64 years, and 1,658(23.30%) households where the householder is over 65 years old.
• The age group of 45 to 64 years exhibits the highest median household income, while the largest number of households falls within the 25 to 44 years bracket. This distribution hints at economic disparities within the city of Winder, 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 Winder median household income by age. You can refer the same here

In 2023, the per capita personal income in Georgia was 59,882 U.S. dollars. This measure of income is calculated as the personal income of the residents of a given area divided by the resident population of the area.

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 Fayetteville. 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 Fayetteville, the median income for all workers aged 15 years and older, regardless of work hours, was $51,922 for males and $37,251 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 28% between the median incomes of males and females in Fayetteville. With women, regardless of work hours, earning 72 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Fayetteville.

- Full-time workers, aged 15 years and older: In Fayetteville, among full-time, year-round workers aged 15 years and older, males earned a median income of $73,776, while females earned $59,925, leading to a 19% gender pay gap among full-time workers. This illustrates that women earn 81 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same 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 Fayetteville, 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 Fayetteville median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the median household income across different racial categories in Dawson County. 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 Dawson County population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 88.88% of the total residents in Dawson County. Notably, the median household income for White households is $88,792. Interestingly, despite the White population being the most populous, it is worth noting that Black or African American households actually reports the highest median household income, with a median income of $226,923. This reveals that, while Whites may be the most numerous in Dawson County, Black or African American households experience greater economic prosperity in terms of median household income.

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Dawson County.
• 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 Dawson County median household income by race. You can refer the same here