Children And Education
Education Levels of Adults by Race/Ethnicity

Increasing





Education Levels of Adults, by Race/Ethnicity, 2014-18

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 does our county compare?

In 2014-18, the share of Lancaster County residents who held a bachelor's degree or higher was highest among Asians, at 41%, followed by whites, 27%, African Americans, 17%, and Hispanics, 13%. At the state level, a higher share of Asians (55%), whites (32%), African American (18%) and Hispanic residents (16%) had college degrees than in Lancaster. The share of people with a Bachelor's degree in the United States was also higher than Lancaster County.

In the City of Lancaster, a similar share of whites (28%) had college degrees compared to Lancaster County as a whole, while a smaller share of Asians (21%), African Americans (15%) and Hispanics (9%) in the city had degrees.

Since 2000, the share of residents without a high school degree declined among all racial and ethnic groups in Lancaster County, ranging from an 18 percentage-point drop among Hispanics to a 7-point drop among whites. All groups, except Asians, had increases in their share of residents who had attended some college or earned an associate's degree.

Among neighboring counties in 2014-18, while racial and ethnic disparities persisted, Chester and Dauphin counties had larger shares of all groups with at least a bachelor's degree. Chester had higher percentages of Asians (82%), African American (27%), Hispanics (17%) and whites (52%) with college degrees. Lebanon had a smaller share of residents with college degrees than Lancaster for all racial groups, with the exception of African Americans which was the same at 17%.

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

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.


Education Levels of Adults, by Race/Ethnicity, 2014-18
AsianBlack or African AmericanHispanicWhite
Pennsylvania13%30%23%24%
Lancaster County14%28%26%22%
Lancaster City5%***25%24%23%
Lancaster County Boroughs
Columbia borough13%***25%**19%***22%
Denver township0%***0%***35%***21%*
East Petersburg borough22%***9%***38%***33%*
Elizabethtown borough12%***29%***32%***28%
Ephrata borough23%***31%***14%***25%
Lititz borough0%***100%***34%***24%
Manheim boroughN/A***N/A***0%***22%*
Marietta boroughN/A***23%***38%***24%
Millersville borough40%***31%***11%***21%*
Mount Joy borough69%***33%***24%***26%
Mountville borough100%***16%***18%***29%*
New Holland borough19%***0%***10%***24%*
Quarryville borough0%***42%***27%***27%
Strasburg borough35%***N/A***26%***26%*
Terre Hill boroughN/A***56%***0%***14%**
Adamstown borough32%***42%***0%***23%*
Akron borough0%***57%***58%***26%
Lancaster County Townships
West Lampeter township35%***30%***18%***25%
Bart township0%***0%***0%***11%*
Brecknock township0%***N/A***0%***20%*
Caernarvon townshipN/A***0%***100%***18%*
Clay township18%***17%***62%***18%*
Colerain townshipN/A***0%***N/A***16%*
Conestoga township0%***N/A***42%***23%
Conoy townshipN/A***N/A***0%***20%*
Drumore townshipN/A***0%***100%***20%*
Earl township0%***100%***53%***11%*
East Cocalico township15%***10%***18%***18%
East Donegal township25%***0%***0%***24%*
East Drumore townshipN/A***0%***N/A***20%*
East Earl township37%***95%***0%***14%*
East Hempfield township14%***39%**36%**22%
East Lampeter township14%***39%**21%***23%
Eden townshipN/A***85%***0%***15%*
Elizabeth township0%***N/A***100%***13%*
Ephrata township23%***3%***17%***22%
Fulton townshipN/A***0%***6%***17%*
Lancaster township4%***23%**40%*23%
Leacock township50%***53%***0%***12%*
Little Britain townshipN/A***0%***N/A***25%*
Manheim township14%***25%***28%*21%
Manor township30%***27%***49%***26%
Martic townshipN/A***N/A***29%***25%
Mount Joy township30%***85%***36%***28%
Paradise townshipN/A***50%***25%***14%*
Penn township0%***45%***38%***20%
Pequea township77%***0%***41%***22%
Providence township28%***N/A***32%***20%*
Rapho township0%***100%***22%***23%
Sadsbury township0%***100%***0%***16%*
Salisbury township18%***21%***33%***15%
Strasburg townshipN/A***N/A***N/A***16%*
Upper Leacock township0%***4%***12%***21%
Warwick township14%***42%***9%***25%
West Cocalico townshipN/A***N/A***48%***25%
West Donegal township0%***27%***52%***23%
West Earl township46%***38%***17%***19%*
West Hempfield township9%***18%***20%***23%
Lebanon County20%**33%*22%22%
York County20%*31%25%25%
Berks County16%*36%22%24%
Chester County7%27%16%20%
Cumberland County13%*33%33%24%
Dauphin County16%29%26%25%

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, 2014-18
AsianBlack or African AmericanHispanicWhite
Pennsylvania36,198265,898109,2431,795,171
Lancaster County1,0833,5987,61171,918
Lancaster City56***1,4573,1005,618
Lancaster County Boroughs
Columbia borough8***197**97***1,332
Denver township0***0***54***530*
East Petersburg borough13***9***75***1,029*
Elizabethtown borough25***75***64***1,873
Ephrata borough19***40***63***2,158
Lititz borough0***38***57***1,581
Manheim borough0***0***0***696*
Marietta borough0***9***18***437
Millersville borough47***27***18***774*
Mount Joy borough52***40***85***1,386
Mountville borough11***19***12***496*
New Holland borough16***0***11***827*
Quarryville borough0***20***31***412
Strasburg borough7***0***25***493*
Terre Hill borough0***5***0***109**
Adamstown borough18***14***0***320*
Akron borough0***4***140***733
Lancaster County Townships
West Lampeter township21***27***98***2,808
Bart township0***0***0***197*
Brecknock township0***0***0***1,006*
Caernarvon township0***0***25***528*
Clay township21***8***45***775*
Colerain township0***0***0***318*
Conestoga township0***0***28***624
Conoy township0***0***0***466*
Drumore township0***0***18***304*
Earl township0***42***60***508*
East Cocalico township15***3***88***1,329
East Donegal township17***0***0***1,220*
East Drumore township0***0***0***501*
East Earl township30***21***0***581*
East Hempfield township83***250**444**3,488
East Lampeter township96***315**179***2,165
Eden township0***22***0***174*
Elizabeth township0***0***8***323*
Ephrata township12***1***58***1,481
Fulton township0***0***6***301*
Lancaster township18***238**878*2,064
Leacock township56***9***0***360*
Little Britain township0***0***0***723*
Manheim township209***205***574*5,138
Manor township104***141***442***3,496
Martic township0***0***10***859
Mount Joy township14***99***94***1,988
Paradise township0***27***17***442*
Penn township0***29***103***1,249
Pequea township30***0***26***762
Providence township11***0***79***992*
Rapho township0***18***53***1,948
Sadsbury township0***11***0***289*
Salisbury township11***10***80***984
Strasburg township0***0***0***405*
Upper Leacock township0***7***56***1,064
Warwick township20***71***38***3,019
West Cocalico township0***0***28***1,153
West Donegal township0***24***32***1,459
West Earl township27***18***29***943*
West Hempfield township16***41***165***2,536
Lebanon County244**598*1,92019,255
York County849*4,6183,90869,322
Berks County635*4,4569,41359,755
Chester County1,2015,0893,11662,373
Cumberland County909*1,8371,59336,721
Dauphin County1,2289,2143,11336,361

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
Prekindergarten Participation Increasing
Student Performance on Grade 3 English Not Applicable
Student Performance on Grade 3 Math Not Applicable
Student Performance on Grade 8 English Not Applicable
Student Performance on Grade 8 Math Not Applicable
Student Performance in Grade 11 English Not Applicable
Student Performance in Grade 11 Math Decreasing
Per-Student Spending Maintaining
Students Receiving Special Education Services Increasing
Rate of Foster Care Admissions Maintaining
Single-Parent Families by Race/Ethnicity Not Applicable
Disengaged Youth Maintaining
Plans of High School Graduates Not Applicable
Enrollment in Local Colleges Decreasing
College Graduation Rates Decreasing
Brain Drain/Gain Increasing
Education Levels of Adults by Race/Ethnicity Not Applicable
Average Charitable Giving Maintaining
Voter Registration Rate Not Applicable
Voter Participation Rate Decreasing
Age of Housing Stock Not Applicable
Violent Crime Rate Maintaining
Incarceration Rate Maintaining
Incarceration Rate by Race/Ethnicity Not Applicable
Population Density Increasing
Air Quality Increasing
Water Use Decreasing
Waterways Impaired by Pollution Not Applicable
Population by Age Not Applicable
Change in Population by Age and Gender Not Applicable
Population by Race/Ethnicity Not Applicable
People with Disabilities Increasing
Foreign-Born Population Increasing
Language Diversity Increasing
Change in Employment by Sector Not Applicable
Sector Share of Total Jobs Not Applicable
Workers by Occupation Not Applicable
Change in Labor Force Maintaining
People Entering/Leaving County/Region for Work Not Applicable
Average Salary by Sector Not Applicable
Change in Average Salary Since 2000 Increasing
Female to Male Earnings Ratio Maintaining
Employer Size Not Applicable
Change in Number of Businesses by Sector Increasing
Change in Total Agricultural Sales Increasing
Spending for Local Government Maintaining
Spending for School Districts Maintaining
Children Living in Poverty Increasing
Children in Poverty by Race/Ethnicity Not Applicable
People Living in Poverty Increasing
People Living in Poverty, by Race/Ethnicity Not Applicable
Veterans Living in Poverty Decreasing
Working Poor Maintaining
Median Household Income by Household Type Not Applicable
Median Household Income, by Race/Ethnicity Not Applicable
Living Wage Not Applicable
Unemployment Rate by Race/Ethnicity Not Applicable
Households Receiving SNAP by Race/Ethnicity Not Applicable
Household Receiving Temporary Assistance Increasing
Students Eligible for Free/Reduced Price Lunch Increasing
Median Home Value Maintaining
Occupied Housing Units Decreasing
Homeownership Rate, by Race/Ethnicity Not Applicable
Cost of Homeownership by Race/Ethnicity Not Applicable
Median Rent Maintaining
Cost of Renting Increasing
Households Without Vehicles Maintaining
Means of Transportation to Work, by Race/Ethnicity Not Applicable
People Without Health Insurance Decreasing
Early Prenatal Care by Mother's Race/Ethnicity Not Applicable
Health Status Maintaining
Prevalence of Mental Illness Maintaining
Adults Who are Overweight or Obese Not Applicable
Mortality Rates Decreasing
Fatal Drug Overdoses Increasing
Cancer Incidence Decreasing
Households With Internet Access Not Applicable
High-Tech Jobs Increasing
STEM Graduates Increasing
Science and Engineering Research and Development Maintaining
Single-Parent Families by Race/Ethnicity Not Applicable
Education Levels of Adults by Race/Ethnicity Not Applicable
Incarceration Rate by Race/Ethnicity Not Applicable
Population by Race/Ethnicity Not Applicable
Children in Poverty by Race/Ethnicity Not Applicable
People Living in Poverty, by Race/Ethnicity Not Applicable
Median Household Income, by Race/Ethnicity Not Applicable
Unemployment Rate by Race/Ethnicity Not Applicable
Households Receiving SNAP by Race/Ethnicity Not Applicable
Homeownership Rate, by Race/Ethnicity Not Applicable
Cost of Homeownership by Race/Ethnicity Not Applicable
Early Prenatal Care by Mother's Race/Ethnicity Not Applicable


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