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.

United States per capita personal income by county (2021) vs. level of education.

Data source for United States per capita personal income by county: https://www.bea.gov/data/income-saving/personal-income-county-metro-and-other-areas

Data source for education level: https://www.ers.usda.gov/data-products/county-level-data-sets/county-level-data-sets-download-data/

bea.gov is the U.S. Bureau of Economic Analysis

usda.gov is the U.S. Department of Agriculture

They are the most recent data available at the moment. Per capita personal income by county data was released in November 2022. Next release should be in Q4 2023.

I cleaned both tables and I merged them with BigQuery

You can find the data viz here: https://public.tableau.com/views/PerCapitaPersonalIncomebyCountyintheUnitedStates2021/Map?:language=en-US&publish=yes&:display_count=n&:origin=viz_share_link

*Note: BEA state per capita personal income statistics are calculated by dividing population into personal income. Check their methodology here https://www.bea.gov/note-capita-personal-income-and-population

Employment income (in 2019 and 2020) by major field of study and highest certificate, diploma or degree, for cities. Includes five-year age groups, for the Pan-Canadian Education Indicators Program (PCEIP).

The 2020-2021 School Neighborhood Poverty Estimates are based on school locations from the 2020-2021 Common Core of Data (CCD) school file and income data from families with children ages 5 to 17 in the U.S. Census Bureau’s 2017-2021 American Community Survey (ACS) 5-year collection. The ACS is a continuous household survey that collects social, demographic, economic, and housing information from the population in the United States each month. The Census Bureau calculates the income-to-poverty ratio (IPR) based on money income reported for families relative to the poverty thresholds, which are determined based on the family size and structure. Noncash benefits (such as food stamps and housing subsidies) are excluded, as are capital gains and losses. The IPR is the percentage of family income that is above or below the federal poverty level. The IPR indicator ranges from 0 to a top-coded value of 999. A family with income at the poverty threshold has an IPR value of 100. The estimates in this file reflect the IPR for the neighborhoods around schools which may be different from the neighborhood conditions of students enrolled in schools.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

Context

A striking graph from the Social Security Administration (https://www.ssa.gov/policy/docs/factsheets/at-a-glance/earnings-men-1988-2018.html) shows that median annual earnings for all men above the age of 20 have decreased since 1988: https://www.ssa.gov/policy/docs/factsheets/at-a-glance/earnings-men-1988-2018.svg" alt="">

I wanted to better understand how educational attainment has played a role in the above trend, and to come up with a model to forecast the future trend for earnings by educational attainment.

As I began looking at the data from the Bureau of Labor Statistics website, there was a striking trend: the median weekly earnings for all groups of people who did not have a bachelors degree or higher had decreased from 1979 levels, in constant 2020 dollars.

Content

I collated data from the US Bureau of Labor Statistics (https://www.bls.gov/webapps/legacy/cpsatab4.htm) and (https://www.bls.gov/cps/cpswktabs.htm) and the US Census Bureau (https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-income-people.html) to create this dataset.

I have omitted details of gender and race, to solely look at the correlation between educational attainment and median weekly earnings over the years. All of the data is for ages 25 and higher unless otherwise stated in the column header.

An important note is that all the earnings data are in constant base 2020 dollars. This removes the effects of inflation and makes it possible to compare the numbers over the years.

The data starts at the year 1960, but unfortunately only overall labor force data, and population percentages of persons with a high school graduation (HSG) and persons with a Bachelors or Higher Degree are available. Median weekly earnings data categorized by educational attainment is available from 1979 onwards, while labor force data i.e., labor force level, labor force participation rate and the employment level by educational attainment is available only from 1992 onwards.

The only columns that have data from 1960 onwards are: (i) overall labor force level, (ii) civilian non-institutional population level, (iii) overall labor force participation rate, (iv) overall employment level, (v) overall percentage of high school graduates, and (vi) overall percentage of persons with a bachelors degree or higher.

Some of the columns can be calculated from other columns, for instance the civilian non-institutional population level can be calculated from the labor force participation rate.

Acknowledgements

All of this data is from the Bureau of Labor Statistics, and the Census Bureau: https://www.bls.gov/webapps/legacy/cpsatab4.htm , https://www.bls.gov/cps/cpswktabs.htm and https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-income-people.html .

A big thank you to all those who worked so hard to collect and organize this data.

Inspiration

The main question is: what is the best way to generate forecasts for median weekly earnings for each educational attainment level?

In 2023, the mean income of women with a doctorate degree in the United States stood at 139,100 U.S. dollars. For men with the same degree, mean earnings stood at 175,500 U.S. dollars. On average in 2023, American men earned 91,590 U.S. dollars, while American women earned 65,987 U.S. dollars.

Dataset Overview 📝

The dataset includes the following key indicators, collected for over 200 countries:

• Government Expenditure on Education (% of GDP): Shows the percentage of a country’s GDP allocated to education.
• Literacy Rate (Adult Total): Represents the percentage of the population aged 15 and above who can read and write.
• Primary Completion Rate: The percentage of children who complete their primary education within the official age group.
• Pupil-Teacher Ratio (Primary and Secondary Education): Indicates the average number of students per teacher at the primary and secondary levels.
• School Enrollment Rates (Primary, Secondary, Tertiary): Reflects the percentage of the relevant age group enrolled in schools across different education levels.

Data Source 🌐

World Bank: This dataset is compiled from the World Bank's educational database, providing reliable, updated statistics on educational progress worldwide.

Potential Use Cases 🔍 This dataset is ideal for anyone interested in:

Educational Research: Understanding how education spending and policies impact literacy, enrollment, and overall educational outcomes. Predictive Modeling: Building models to predict educational success factors, such as completion rates and literacy. Global Education Analysis: Analyzing trends in global education systems and how different countries allocate resources to education. Policy Development: Helping governments and organizations make data-driven decisions regarding educational reforms and funding.

Key Questions You Can Explore 🤔

How does government expenditure on education correlate with literacy rates and school enrollment across different regions? What are the trends in pupil-teacher ratios over time, and how do they affect educational outcomes? How do education indicators differ between low-income and high-income countries? Can we predict which countries will achieve universal primary education based on current trends?

Important Notes ⚠️ - Missing Data: Some values may be missing for certain years or countries. Consider using techniques like forward filling or interpolation when working with time series models. - Data Limitations: This dataset provides global averages and may not capture regional disparities within countries.

Employment income (in 2019 and 2020) by highest certificate, diploma or degree, for census divisions and municipalities.

Educational status and labour market status of people aged 16 to 24 years, by sex, in and out of full-time education, UK, rolling three-monthly figures published monthly, seasonally adjusted. Labour Force Survey. These are official statistics in development.

Net-Interest-Income Time Series for American Public Education Inc. American Public Education, Inc., together with its subsidiaries, provides online and campus-based postsecondary education and career learning in the United States. It operates through three segments: American Public University System, Rasmussen University, and Hondros College of Nursing. The company offers 182 degree programs and 136 certificate programs in various fields of study, including nursing, national security, military studies, intelligence, homeland security, business, health science, information technology, justice studies, education, and liberal arts; and career learning opportunities in leadership, finance, human resources, and other fields of study critical to the federal government workforce. It also provides nursing-and health sciences-focused postsecondary education, pre-licensure nursing programs, diploma in practical nursing, and an associate degree in nursing. The company was incorporated in 1991 and is headquartered in Charles Town, West Virginia.

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.

This file contains unrounded data on income of local authority maintained schools. It includes local authority, regional and national data. It was collected via the Consistent Financial reporting data collection.

Detailed labour market outcomes by educational characteristics, including detailed occupation, hours and weeks worked and employment income.

Number and percentage of children aged 1 to 17 for selected health indicators, by household income quintile and highest level of parental education, Canada (excluding Territories) and provinces.

Neighborhood; Median household income; Unemployed (ages GE 16); Families below 185% FPL; Children (ages 0-17) below 185% FPL; Children (ages 3-4) enrolled in preschool or nursery school; Less than high school; High school graduate; Some college or associates degree; College graduate or higher; High school graduate or less. Percentages unless otherwise noted. Source information provided at: https://www.sccgov.org/sites/phd/hi/hd/Documents/City%20Profiles/Methodology/Neighborhood%20profile%20methodology_082914%20final%20for%20web.pdf

Characteristics and median employment income of postsecondary graduates five years after graduation, by educational qualification (Classification of programs and credentials - professional degree variant), field of study (Classification of Instructional Programs (CIP) Canada 2016 - STEM (science, technology, engineering and mathematics and computer sciences) and BHASE (business, humanities, health, arts, social science and education) groupings), gender, age group and status of student in Canada (cross-sectional analysis).

Net-Income Time Series for Strategic Education Inc. Strategic Education, Inc. provides education services through campus-based and online post-secondary education, and programs to develop job-ready skills. The company operates through three segments: U.S. Higher Education, Australia/New Zealand, and Education Technology Services. It operates Strayer University that offers undergraduate and graduate degree programs in business, criminal justice, education, health services, information technology, and public administration at physical campuses located in the eastern United States, as well as through online; non-degree web and mobile application development courses through Hackbright Academy and Devmountain; and MBA online through its Jack Welch Management Institute. In addition, the company operates Capella University that provides post-secondary education; Torrens University, which offers undergraduate, graduate, higher degree by research, and specialized degree courses primarily in business, design and creative technology, health, hospitality, and education fields through online and on physical campuses located in Australia; Think Education, a vocational training organization; and Media Design School, which provides industry-endorsed courses in 3D animation and visual effects, game art and programming, graphic and motion design, digital media artificial intelligence, and creative advertising in New Zealand. It offers Workforce Edge, a platform which provides employers a full-service education benefits administration solution; and Sophia Learning, which offers low-cost online general education-level courses. Strategic Education, Inc. was founded in 1892 and is headquartered in Herndon, Virginia.

This dataset accompanies the tables ‘Household income and saving in the National Accounts: distributions by income quintile’ and ‘Household consumption in the National Accounts: distributions by income quintile’ and presents the number of individuals belonging to households in each quintile broken down by the highest level of education achieved.

   Households are grouped into income quintiles on the basis of their equivalised disposable income, ranked from lowest to highest, i.e., the first quintile represents the 20% households with the lowest equivalised disposable income and the fifth quintile the 20% households with the highest. Equivalisation means that results for each household have been recalculated on the basis of its consumption needs, in order to produce comparable results across households of different size and composition. <br><br>

   The education levels are derived on the basis of the International Standard Classification of Education (ISCED) which distinguishes the following categories: 0) less than primary education, 1) primary education, 2) lower secondary education, 3) upper secondary education, 4) post-secondary non-tertiary education, 5) short-cycle tertiary education, 6) bachelor’s or equivalent level, 7) master’s or equivalent level, 8) doctoral or equivalent level. <br><br>

   The default view of this table is for a single country (‘Reference area’ filter) and single year (‘Time period’ filter). In cases where countries appear to be greyed-out, data may be available for earlier years, and these can be selected by selecting a different start and end year in the ‘Time period’ filter. <br><br>

   For more information on the (compilation of) these results, please see the <a href="https://www.oecd.org/sdd/na/household-distributional-results-in-line-with-national-accounts-experimental-statistics.htm"> webpage on household distributional results </a>.

This file contains national level rounded data on income of local authority maintained schools. It was collected via the Consistent Financial reporting data collection.