Education
Education Levels of Adults, by Race/Ethnicity, 2015-19





Education Levels of Adults, by Race/Ethnicity, 2015-19

What does this measure?

The number of residents with a particular level of education in a region, expressed as a percentage of all residents 25 and older, broken down by race and ethnicity.

Why is this important?

An educated population makes a more attractive workforce and is better prepared to instruct the next generation of residents. High educational attainment represents a region's investment in human capital and preparation for long-term growth. There are persistent gaps in academic achievement among students of different races, ethnicities and incomes, and this is likely reflected in levels of educational attainment.

How is our county performing?

In 2015-19, the share of Berks County residents who held a bachelor's degree or higher was highest among Asians, at 47%, followed by whites, 26%, African Americans, 15%, and Hispanics, 11%. At the state level, a higher share of Asians (56%), whites (32%), African American (19%) and Hispanic residents (16%) had college degrees than in Berks. The share of people with a Bachelor's degree in the United States was also higher than Berks County. In the City of Reading, a smaller share of residents of all races held a bachelor's degree or higher than in the county as a whole (12% of whites and 8% of African Americans and Hispanics).

Since 2000, the share of residents without a high school degree declined among all racial and ethnic groups in Berks County, ranging from a 9 percentage-point drop among whites to about 19 points among Hispanics. All groups had increases in their share of residents who had attended some college or earned an associate's degree.

Among neighboring counties in 2015-19, while racial and ethnic disparities persisted, Chester, Lehigh and Montgomery counties had larger shares of all groups with at least a bachelor's degree. Chester had higher percentages of Asians (83%) and whites (53%) with bachelor's degrees. Montgomery had higher percentages of African Americans (32%) and Hispanics (29%) with bachelor's degrees. Lancaster had similar education levels to Berks. Reading had a smaller share of residents with college degrees than Berks for all racial groups.

Why do these disparities exist?

There are a variety of factors believed to contribute to disparities in educational attainment. School systems in the United States are highly segregated, and students of color disproportionately attend schools with high proportions of low-income students who may not have benefited from early learning opportunities at the same rate as other students. Schools also have different levels of resources ranging from qualified/experienced teachers to advanced courses to facilities and technology, and schools with large Black and Latino populations often have lower levels. In addition, teachers across all school systems tend to be disproportionately white, and teaching practices and curriculum may not be culturally relevant to students of color. Low staff expectations at racially and economically segregated schools also contribute disparities in educational attainment. The accumulation of inequities leads to lower graduation rates and college matriculation, with college affordability acting as another barrier. When Black and Latino students enter higher education institutions, they are less likely to attain a college a degree given weaker academic preparation and financial hardship.

Notes about the data

For additional detail as to how the Berks County regions are defined and which boroughs and townships are included in each, see the About Us page.

Adults are people 25 and older. The multi-year figures are from the Census Bureau's American Community Survey. The bureau combined five years of responses to the survey to provide estimates for smaller geographic areas and increase the precision of its estimates. However, because the information came from a survey, the samples responding to the survey were not always large enough to produce reliable results, especially in small geographic areas. CGR has noted on data tables the estimates with relatively large margins of error. Estimates with three asterisks have the largest margins, plus or minus 50% or more of the estimate. Two asterisks mean plus or minus 35%-50%, and one asterisk means plus or minus 20%-35%. For all estimates, the confidence level is 90%, meaning there is 90% probability the true value (if the whole population were surveyed) would be within the margin of error (or confidence interval). The survey provides data on characteristics of the population that used to be collected only during the decennial census. Data for this indicator are released annually in December.

There may be additional research available on this topic. Click on Reports and Resources to learn more.


Education Levels of Adults, by Race/Ethnicity, 2015-19
AsianBlack or African AmericanHispanicWhite
United States18%33%24%29%
Pennsylvania13%30%23%24%
Berks County16%**37%23%25%
Berks County Regions
Central21%****36%21%23%
Northeast28%******43%******45%****25%
South11%******37%**30%25%
Southeast7%******48%******29%******26%
West24%******31%****21%**24%
Reading city23%****35%20%20%
Berks County Peers
Chester County7%28%17%20%
Lancaster County15%27%27%22%
Lebanon County21%****33%**24%22%
Lehigh County16%34%27%26%
Montgomery County13%28%21%22%
Schuylkill County27%****24%22%26%

Source: U.S. Census Bureau
Notes: Adults are people 25 and older. Multiyear results are from rolling American Community Survey. * Margin of error between 20% & 35% of estimate; ** margin of error between 35% & 50%; *** margin of error greater than 50%. The Census Bureau asks people to identify their race (white, African-American, etc.) separate from their ethnicity (Hispanic or non-Hispanic). So the totals for these categories cannot be added together, as people show up in both a racial and ethnic group.




Number of Adults, by Education Level and Race/Ethnicity, 2015-19
AsianBlack or African AmericanHispanicWhite
United States2,316,5278,692,6508,122,64448,446,126
Pennsylvania37,166269,376116,1311,802,404
Berks County636**4,75910,14860,668
Berks County Regions
Central182****2,7966,94911,003
Northeast82******192******549****10,851
South213******1,210**1,92217,714
Southeast28******293******290******10,185
West131******268****438**10,925
Reading city120****2,3125,9515,916
Berks County Peers
Chester County1,3715,2423,46461,607
Lancaster County1,1803,5658,03973,421
Lebanon County254****666**2,19819,152
Lehigh County1,3745,24612,98053,547
Montgomery County5,51214,2744,803101,370
Schuylkill County165****85772325,715

Source: U.S. Census Bureau
Notes: Adults are people 25 and older. Multiyear results are from rolling American Community Survey. * Margin of error between 20% & 35% of estimate; ** margin of error between 35% & 50%; *** margin of error greater than 50%. The Census Bureau asks people to identify their race (white, African-American, etc.) separate from their ethnicity (Hispanic or non-Hispanic). So the totals for these categories cannot be added together, as people show up in both a racial and ethnic group.




INDICATORS TREND | BERKS COUNTY
Adults Who are Overweight or Obese Not Applicable
Students in K-6 Overweight or Obese Not Applicable
Students in 7-12 Overweight or Obese Not Applicable
Physically Inactive Adults Not Applicable
Students Eligible for Free/Reduced Price Lunch Increasing
Early Prenatal Care Increasing
Early Prenatal Care by Mother's Race/Ethnicity Not Applicable
Children Living in Poverty Increasing
Children Living in Poverty, by Race/Ethnicity Not Applicable
Single-Parent Families Increasing
Single-Parent Families by Race/Ethnicity Not Applicable
Disengaged Youth Decreasing
Live Births to Teen Mothers Decreasing
Population by Age Not Applicable
Children with Elevated Blood Lead Levels Maintaining
Change in Population by Age and Gender Not Applicable
Change in Total Population by Race/Ethnicity Not Applicable
Households by type Not Applicable
Foreign-Born Population Increasing
Seniors Living Alone Maintaining
Language Diversity Increasing
Unemployment Rate Decreasing
Change in Labor Force Decreasing
Employment to Population ratio Decreasing
Change in Jobs by Sector Not Applicable
Sector Share of Total Jobs Not Applicable
Average Salary by Sector Not Applicable
Change in Average Salary by Sector Not Applicable
People Entering/Leaving County/Region for Work Not Applicable
Public Assistance Maintaining
Spending for Local Governments Maintaining
Spending for Counties Maintaining
Spending for School Districts Maintaining
Prekindergarten Participation Increasing
English Language Learners Increasing
Students Receiving Special Education Services Increasing
Per Student Spending Maintaining
High School Cohort Graduation Rate Increasing
Education Levels of Adults Not Applicable
Education Levels of Adults, by Race/Ethnicity Not Applicable
Brain Drain/Gain Maintaining
Plans of High School Graduates Not Applicable
Enrollment in Local Colleges Decreasing
Median Household Income Maintaining
Median Household Income by Household Type Not Applicable
Living Wage Not Applicable
People Living in Poverty Increasing
Working Poor Maintaining
People Receiving Federal Food Assistance Increasing
People Receiving Supplemental Security Income Increasing
Health Status Not Applicable
People Enrolled in Medicaid Managed Care Increasing
People Without Health Insurance Decreasing
Cancer Incidence Decreasing
Prevalence of Mental Illness Maintaining
Vacant Housing Units Increasing
Homeownership Rates Decreasing
Cost of Homeownership Maintaining
Cost of Homeownership, by Race/Ethnicity Not Applicable
Cost of Rent Increasing
Cost of Rent, by Race/Ethnicity Not Applicable
Single-Family Home Sales Increasing
Median Single-Family Home Sale Price Maintaining
Tourism Spending Maintaining
Voter Registration Rate Decreasing
Voter Participation Rate Decreasing
Average Charitable Giving Maintaining
Contributions as a Percentage of Income Maintaining
Households With Internet Access Not Applicable
Arts, Entertainment and Recreation Establishments Maintaining
Toxic Chemical Releases Decreasing
Violent Crimes Maintaining
Property Crimes Decreasing
Incarceration Rates Maintaining
Drug Abuse Offenses Increasing
Drug Abuse Arrests Increasing
Protection from Domestic Abuse Maintaining
Average Travel Time to Work Increasing
Crashes Involving Alcohol Decreasing
Households Without Vehicles Decreasing