Graph and download economic data for Employed full time: Wage and salary workers: Less than a High School diploma: 25 years and over: Black or African American: Men (LEU0252937800A) from 2000 to 2024 about secondary schooling, African-American, secondary, 25 years +, full-time, males, salaries, workers, education, wages, employment, and USA.

This statistic shows the percentage of the Black, non-Hispanic population aged between 25 and 29 years with a high school diploma or higher in the United States from 1975 to 2022, by gender. In 2022, about **** percent of Black, non-Hispanic females had attained at least a high school diploma in the United States compared to **** percent of Black, non-Hispanic males.

Financial overview and grant giving statistics of African American Male Educational Network and Development

Graph and download economic data for Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Some college or associate degree: 25 years and over: Black or African American: Men (LEU0254932400A) from 2000 to 2024 about no college, associate degree, second quartile, African-American, 25 years +, full-time, males, salaries, workers, earnings, education, wages, median, employment, and USA.

Graph and download economic data for Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: High School graduates, no college: 25 years and over: Black or African American: Men (LEU0252938700A) from 2000 to 2024 about no college, second quartile, secondary schooling, African-American, secondary, 25 years +, full-time, males, salaries, workers, earnings, education, wages, median, employment, and USA.

In 2022, about 37.7 percent of the U.S. population who were aged 25 and above had graduated from college or another higher education institution, a slight decline from 37.9 the previous year. However, this is a significant increase from 1960, when only 7.7 percent of the U.S. population had graduated from college. Demographics Educational attainment varies by gender, location, race, and age throughout the United States. Asian-American and Pacific Islanders had the highest level of education, on average, while Massachusetts and the District of Colombia are areas home to the highest rates of residents with a bachelor’s degree or higher. However, education levels are correlated with wealth. While public education is free up until the 12th grade, the cost of university is out of reach for many Americans, making social mobility increasingly difficult. Earnings White Americans with a professional degree earned the most money on average, compared to other educational levels and races. However, regardless of educational attainment, males typically earned far more on average compared to females. Despite the decreasing wage gap over the years in the country, it remains an issue to this day. Not only is there a large wage gap between males and females, but there is also a large income gap linked to race as well.

In 2023, the mean income of Black Bachelor's degree holders was ****** U.S. dollars, compared to ****** U.S. dollars for White Americans with a Bachelor's degree.

United States - Employed full time: Wage and salary workers: High School graduates, no college: 25 years and over: Black or African American: Men was 2329.00000 Thous. of Persons in January of 2024, according to the United States Federal Reserve. Historically, United States - Employed full time: Wage and salary workers: High School graduates, no college: 25 years and over: Black or African American: Men reached a record high of 2376.00000 in January of 2022 and a record low of 1738.00000 in January of 2010. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Employed full time: Wage and salary workers: High School graduates, no college: 25 years and over: Black or African American: Men - last updated from the United States Federal Reserve on October of 2025.

United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: High School graduates, no college: 25 years and over: Black or African American: Men was 870.00000 $ in January of 2024, according to the United States Federal Reserve. Historically, United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: High School graduates, no college: 25 years and over: Black or African American: Men reached a record high of 870.00000 in January of 2024 and a record low of 491.00000 in January of 2000. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: High School graduates, no college: 25 years and over: Black or African American: Men - last updated from the United States Federal Reserve on November of 2025.

Black men without a college degree have seen especially strong gains in employment and wages during the pandemic recovery.

Historical Dataset of Man Middle School is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2003-2023),Total Classroom Teachers Trends Over Years (2003-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (2003-2023),Hispanic Student Percentage Comparison Over Years (2013-2022),Black Student Percentage Comparison Over Years (2003-2023),White Student Percentage Comparison Over Years (2003-2023),Two or More Races Student Percentage Comparison Over Years (2019-2023),Diversity Score Comparison Over Years (2003-2023),Free Lunch Eligibility Comparison Over Years (2004-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2003-2012),Reading and Language Arts Proficiency Comparison Over Years (2010-2022),Math Proficiency Comparison Over Years (2012-2023),Science Proficiency Comparison Over Years (2021-2022),Overall School Rank Trends Over Years (2012-2023)

The purpose of this data collection was to provide a more accurate measure the racial/ethnic enrollment in postsecondary institutions in the United States. The National Center for Education Statistics (NCES) collects racial/ethnic enrollment data from higher education institutions on a biennial basis. Some institutions do not report this data, and their "unknown" categories have previously been distributed in direct proportion to the "knowns." This resulted in lower than accurate figures for the racial/ethnic categories. With the advent of the Integrated Postsecondary Education Data System (IPEDS), NCES has attempted to eliminate this problem by distributing all race/ethnicity unknown students. This is done in a two-stage process. First, the differences between reported totals and racial/ethnic details are allocated on a gender and institutional basis by distributing the differences in direct proportion to reported distributions. The second stage distribution is designed to eliminate the remaining "race/ethnicity" unknowns. The procedure is to accumulate the reported racial/ethnic total enrollments by state, level, control, and gender, calculate the percentage distributions, and apply these percentages to the reported total enrollments of institutional respondents (in the same state, level, and control) that did not supply race/ethnicity detail. In addition, the original "race unknown" data were also left unaltered in order to provide data for those who wish to review numbers actually distributed. The racial/ethnic status was broken down into non-resident alien, Black non-Hispanic, American Indian or Alaskan Native, Asian or Pacific Islander, Hispanic, and White non-Hispanic. Variables include the educational level of all male/female full-time and part-time students enrolled in courses for credit at the institution. The unit of analysis is the postsecondary institution.

This map shows the percent of Black or African American females that have less than a high school diploma by state, county, and tract using American Community Survey data. The pop-up is configured to show the percent and count of Black or African American females that have less than a high school diploma, total number of Black or African American females, and a chart comparing female and male Black or African American education levels.Map notes: Tracts and Counties that have no Black or African American females have been filtered out of the layer. Remove the filter in the layer properties to draw these areas. Data is from the American Community Survey (ACS) 5 year estimates available in state, county, and tract geographies. This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.You can find the previous version of this map here.

Abstract: This article seeks to better understand some artistic representations of black men in the Western arts (from the 15th the 19th century). The analysis refers to the education field, aiming to understand how the discourse of difference is constructed, also, through art. Examples of artistic works in this paper are: Dürer (1471-1528), Rubens (1577-1640), Debret (1768-1848) and Rugendas (1802-1858). These are all important artists within the history of Western art. It is intended, through the works analyzed, to understand the images of the black man represented in portrait style. These artworks are Albrecht Dürer's Head of a Negro; Head of a Black Man, by Peter Paul Rubens; Different Black Nations, Jean-Baptiste Debret; and Mozambique, by Johann Moritz Rugendas.

College sports are very popular in the United States and the championships are organized in divisions around different sports sanctioned mainly by the NCAA, the largest college sports organization. In 2022, an estimated **** percent of male student athletes in United States were white, while **** percent were African American.

United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Some college or associate degree: 25 years and over: Black or African American: Men was 1028.00000 $ in January of 2024, according to the United States Federal Reserve. Historically, United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Some college or associate degree: 25 years and over: Black or African American: Men reached a record high of 1028.00000 in January of 2024 and a record low of 560.00000 in January of 2000. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Some college or associate degree: 25 years and over: Black or African American: Men - last updated from the United States Federal Reserve on November of 2025.

U.S. citizens with a professional degree had the highest median household income in 2023, at 172,100 U.S. dollars. In comparison, those with less than a 9th grade education made significantly less money, at 35,690 U.S. dollars. Household income The median household income in the United States has fluctuated since 1990, but rose to around 70,000 U.S. dollars in 2021. Maryland had the highest median household income in the United States in 2021. Maryland’s high levels of wealth is due to several reasons, and includes the state's proximity to the nation's capital. Household income and ethnicity The median income of white non-Hispanic households in the United States had been on the rise since 1990, but declining since 2019. While income has also been on the rise, the median income of Hispanic households was much lower than those of white, non-Hispanic private households. However, the median income of Black households is even lower than Hispanic households. Income inequality is a problem without an easy solution in the United States, especially since ethnicity is a contributing factor. Systemic racism contributes to the non-White population suffering from income inequality, which causes the opportunity for growth to stagnate.

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Context

The gender pay gap or gender wage gap is the average difference between the remuneration for men and women who are working. Women are generally considered to be paid less than men. There are two distinct numbers regarding the pay gap: non-adjusted versus adjusted pay gap. The latter typically takes into account differences in hours worked, occupations were chosen, education, and job experience. In the United States, for example, the non-adjusted average female's annual salary is 79% of the average male salary, compared to 95% for the adjusted average salary.

The reasons link to legal, social, and economic factors, and extend beyond "equal pay for equal work".

The gender pay gap can be a problem from a public policy perspective because it reduces economic output and means that women are more likely to be dependent upon welfare payments, especially in old age.

This dataset aims to replicate the data used in the famous paper "The Gender Wage Gap: Extent, Trends, and Explanations", which provides new empirical evidence on the extent of and trends in the gender wage gap, which declined considerably during the 1980–2010 period.

Citation

fedesoriano. (January 2022). Gender Pay Gap Dataset. Retrieved [Date Retrieved] from https://www.kaggle.com/fedesoriano/gender-pay-gap-dataset.

Content

There are 2 files in this dataset: a) the Panel Study of Income Dynamics (PSID) microdata over the 1980-2010 period, and b) the Current Population Survey (CPS) to provide some additional US national data on the gender pay gap.

PSID variables:

NOTES: THE VARIABLES WITH fz ADDED TO THEIR NAME REFER TO EXPERIENCE WHERE WE HAVE FILLED IN SOME ZEROS IN THE MISSING PSID YEARS WITH DATA FROM THE RESPONDENTS’ ANSWERS TO QUESTIONS ABOUT JOBS WORKED ON DURING THESE MISSING YEARS. THE fz variables WERE USED IN THE REGRESSION ANALYSES THE VARIABLES WITH A predict PREFIX REFER TO THE COMPUTATION OF ACTUAL EXPERIENCE ACCUMULATED DURING THE YEARS IN WHICH THE PSID DID NOT SURVEY THE RESPONDENTS. THERE ARE MORE PREDICTED EXPERIENCE LEVELS THAT ARE NEEDED TO IMPUTE EXPERIENCE IN THE MISSING YEARS IN SOME CASES. NOTE THAT THE VARIABLES yrsexpf, yrsexpfsz, etc., INCLUDE THESE COMPUTATIONS, SO THAT IF YOU WANT TO USE FULL TIME OR PART TIME EXPERIENCE, YOU DON’T NEED TO ADD THESE PREDICT VARIABLES IN. THEY ARE INCLUDED IN THE DATA SET TO ILLUSTRATE THE RESULTS OF THE COMPUTATION PROCESS. THE VARIABLES WITH AN orig PREFIX ARE THE ORIGINAL PSID VARIABLES. THESE HAVE BEEN PROCESSED AND IN SOME CASES RENAMED FOR CONVENIENCE. THE hd SUFFIX MEANS THAT THE VARIABLE REFERS TO THE HEAD OF THE FAMILY, AND THE wf SUFFIX MEANS THAT IT REFERS TO THE WIFE OR FEMALE COHABITOR IF THERE IS ONE. AS SHOWN IN THE ACCOMPANYING REGRESSION PROGRAM, THESE orig VARIABLES AREN’T USED DIRECTLY IN THE REGRESSIONS. THERE ARE MORE OF THE ORIGINAL PSID VARIABLES, WHICH WERE USED TO CONSTRUCT THE VARIABLES USED IN THE REGRESSIONS. HD MEANS HEAD AND WF MEANS WIFE OR FEMALE COHABITOR.

1. intnum68: 1968 INTERVIEW NUMBER
2. pernum68: PERSON NUMBER 68
3. wave: Current Wave of the PSID
4. sex: gender SEX OF INDIVIDUAL (1=male, 2=female)
5. intnum: Wave-specific Interview Number
6. farminc: Farm Income
7. region: regLab Region of Current Interview
8. famwgt: this is the PSID’s family weight, which is used in all analyses
9. relhead: ER34103L this is the relation to the head of household (10=head; 20=legally married wife; 22=cohabiting partner)
10. age: Age
11. employed: ER34116L Whether or not employed or on temp leave (everyone gets a 1 for this variable, since our wage analyses use only the currently employed)
12. sch: schLbl Highest Year of Schooling
13. annhrs: Annual Hours Worked
14. annlabinc: Annual Labor Income
15. occ: 3 Digit Occupation 2000 codes
16. ind: 3 Digit Industry 2000 codes
17. white: White, nonhispanic dummy variable
18. black: Black, nonhispanic dummy variable
19. hisp: Hispanic dummy variable
20. othrace: Other Race dummy variable
21. degree: degreeLbl Agent's Degree Status (0=no college degree; 1=bachelor’s without advanced degree; 2=advanced degree)
22. degupd: degreeLbl Agent's Degree Status (Updated with 2009 values)
23. schupd: schLbl Schooling (updated years of schooling)
24. annwks: Annual Weeks Worked
25. unjob: unJobLbl Union Coverage dummy variable
26. usualhrwk: Usual Hrs Worked Per Week
27. labincbus: Labor Income from...

In 2023, 17.8 percent of Black families with a single father were living below the poverty line in the United States. Poverty is the state of one who lacks a certain amount of material possessions or money. Absolute poverty or destitution is inability to afford basic human needs, which commonly includes clean and fresh water, nutrition, health care, education, clothing and shelter.

Author's Note 2019/04/20: Revisiting this project, I recently discovered the incredibly comprehensive API produced by the Urban Institute. It achieves all of the goals laid out for this dataset in wonderful detail. I recommend that users interested pay a visit to their site.

Context

This dataset is designed to bring together multiple facets of U.S. education data into one convenient CSV (states_all.csv).

Contents

• states_all.csv: The primary data file. Contains aggregates from all state-level sources in one CSV.

• output_files/states_all_extended.csv: The contents of states_all.csv with additional data related to race and gender.

Column Breakdown

Identification

• PRIMARY_KEY: A combination of the year and state name.
• YEAR
• STATE

Enrollment

A breakdown of students enrolled in schools by school year.

• GRADES_PK: Number of students in Pre-Kindergarten education.

• GRADES_4: Number of students in fourth grade.

• GRADES_8: Number of students in eighth grade.

• GRADES_12: Number of students in twelfth grade.

• GRADES_1_8: Number of students in the first through eighth grades.

• GRADES 9_12: Number of students in the ninth through twelfth grades.

• GRADES_ALL: The count of all students in the state. Comparable to ENROLL in the financial data (which is the U.S. Census Bureau's estimate for students in the state).

The extended version of states_all contains additional columns that breakdown enrollment by race and gender. For example:

• G06_A_A: Total number of sixth grade students.

• G06_AS_M: Number of sixth grade male students whose ethnicity was classified as "Asian".

• G08_AS_A_READING: Average reading score of eighth grade students whose ethnicity was classified as "Asian".

The represented races include AM (American Indian or Alaska Native), AS (Asian), HI (Hispanic/Latino), BL (Black or African American), WH (White), HP (Hawaiian Native/Pacific Islander), and TR (Two or More Races). The represented genders include M (Male) and F (Female).

Financials

A breakdown of states by revenue and expenditure.

• ENROLL: The U.S. Census Bureau's count for students in the state. Should be comparable to GRADES_ALL (which is the NCES's estimate for students in the state).

• TOTAL REVENUE: The total amount of revenue for the state.

  • FEDERAL_REVENUE
  • STATE_REVENUE
  • LOCAL_REVENUE

• TOTAL_EXPENDITURE: The total expenditure for the state.

  • INSTRUCTION_EXPENDITURE

  • SUPPORT_SERVICES_EXPENDITURE

  • CAPITAL_OUTLAY_EXPENDITURE

  • OTHER_EXPENDITURE

Academic Achievement

A breakdown of student performance as assessed by the corresponding exams (math and reading, grades 4 and 8).

• AVG_MATH_4_SCORE: The state's average score for fourth graders taking the NAEP math exam.

• AVG_MATH_8_SCORE: The state's average score for eight graders taking the NAEP math exam.

• AVG_READING_4_SCORE: The state's average score for fourth graders taking the NAEP reading exam.

• AVG_READING_8_SCORE: The state's average score for eighth graders taking the NAEP reading exam.

Data Processing

The original sources can be found here:

# Enrollment
https://nces.ed.gov/ccd/stnfis.asp
# Financials
https://www.census.gov/programs-surveys/school-finances/data/tables.html
# Academic Achievement
https://www.nationsreportcard.gov/ndecore/xplore/NDE

Data was aggregated using a Python program I wrote. The code (as well as additional project information) can be found [here][1].

Methodology Notes

• Spreadsheets for NCES enrollment data for 2014, 2011, 2010, and 2009 were modified to place key data on the same sheet, making scripting easier.

• The column 'ENROLL' represents the U.S. Census Bureau data value (financial data), while the column 'GRADES_ALL' represents the NCES data value (demographic data). Though the two organizations correspond on this matter, these values (which are ostensibly the same) do vary. Their documentation chalks this up to differences in membership (i.e. what is and is not a fourth grade student).

• Enrollment data from NCES has seen a number of changes across survey years. One of the more notable is that data on student gender does not appear to have been collected until 2009. The information in states_all_extended.csv reflects this.

• NAEP test score data is only available for certain years

• The current version of this data is concerned with state-level patterns. It is the author's hope that future versions will allow for school district-level granularity.

Acknowledgements

Data is sourced from the U.S. Census Bureau and the National Center for Education Statistics (NCES).

Licensing Notes

The licensing of these datasets state that it must not be us...