Trends in High School Dropout and Completion Rates in the United States

Dropping out of high school is related to a number of negative outcomes. According to data from the Census Bureau’s 2017 Current Population Survey (CPS), the median earnings of adults ages 25 through 34 who worked full time, year round and who had not completed high school were lower than the earnings of those with higher levels of educational attainment.¹ For example, median earnings for full-time workers ages 25 through 34 who had not completed high school ($26,000) were lower than those of workers whose highest education level was high school completion ($32,000), an associate’s degree ($39,000), or a bachelor’s or higher degree ($55,000). Among 25- to 34-year-olds in the labor force, the unemployment rate for high school dropouts (13 percent) was higher than the unemployment rate of those whose highest level of educational attainment was a high school credential (7 percent).² In addition, dropouts age 25 and older were reported being in worse health than adults who were not dropouts, regardless of income (Pleis, Ward, and Lucas 2010). Dropouts also make up disproportionately higher percentages of the nation’s institutionalized population than of the nation’s noninstitutionalized population.³ Relative to individuals who complete high school, the average high school dropout costs the economy approximately $272,000 over his or her lifetime in terms of lower tax contributions, higher reliance on Medicaid and Medicare, higher rates of criminal activity, and higher reliance on welfare (Levin and Belfield 2007).⁴

This report builds upon a series of National Center for Education Statistics (NCES) reports on high school dropout and completion rates that began in 1988. It provides the most recent year of data available for each of the dropout and completion rates, summarizes longterm trends, and examines the characteristics of high school dropouts and completers. Five rates are presented to provide a broad perspective on high school dropouts and completers in the United States: the event dropout rate, the status dropout rate, the status completion rate, the adjusted cohort graduation rate, and the averaged freshman graduation rate. Each rate contributes unique information.

Rates Featured in this Report

• The event dropout rate (Indicator 1) is the percentage of 15- to 24-year-olds in grades 10 through 12 who leave high school between the beginning of one school year and the beginning of the next without earning a high school diploma or an alternative credential such as a GED. This report presents a national event dropout rate for students attending public or private schools using data from the CPS. Event dropout rates can be used to track annual changes in the dropout behavior of students in the U.S. education system. The state-level event dropout rates for public high school students published as part of the Common Core of Data (CCD) were not available in time for use in this report.⁵
• The status dropout rate (Indicator 2) reports the percentage of individuals in a given age range who are not in school (public or private) and have not earned a high school diploma or an alternative credential. This report presents status dropout rates calculated using both CPS data and data from the American Community Survey (ACS). Over 40 years of data are available for the CPS. The ACS, on the other hand, is available only for more recent years, although it covers a broader population and can be used to compute dropout rates for smaller population subgroups. Because the status dropout rate focuses on an overall age group (as opposed to individuals enrolled in school during a particular year), it can be used to study general population issues.
• The status completion rate (Indicator 3) measures the percentage of individuals in a given age range who are not currently enrolled in high school and who have earned a high school diploma or an alternative credential, regardless of when or where the credential was earned.⁶ The rate is calculated using CPS data. It focuses on an overall age group, as opposed to individuals in the U.S. education system; thus, it can be used to study general population issues.⁷
• The adjusted cohort graduation rate (ACGR) (Indicator 4) is the percentage of public high school students in a specific cohort who graduate with a regular diploma within 4 years of starting 9th grade. Students who enter 9th grade (or the earliest high school grade) for the first time form a cohort that is “adjusted” by adding any students who subsequently transfer into the cohort and subtracting any students who subsequently transfer out, emigrate to another country, or die. The ACGR is calculated by state education agencies (SEAs) and submitted to the U.S. Department of Education through the EDFacts submission system.
• The averaged freshman graduation rate (AFGR) (Indicator 5) provides an estimate of the cohort graduation rate for public high school students. The AFGR uses aggregated counts of students by grade and the overall diploma count, as opposed to individual student-level data, to estimate an on-time graduation rate. NCES calculates the AFGR using enrollment and diploma counts submitted by SEAs through the CCD collection. While the AFGR is not as accurate as the ACGR, it can be estimated annually as far back as the 1960s.⁸

More information about data sources and calculations is provided briefly in the body of the report, with more detail provided in appendixs A and B.

Data Sources

As noted above, the data presented in this report are drawn from the annual October CPS, ACS, EDFacts, and CCD collections. CPS data are collected through household interviews and are representative of the civilian, noninstitutionalized population in the United States, including students attending public and private schools. The ACS collects data on the U.S. resident population through interviews with households and persons in group quarters facilities. The individuals in group quarters facilities surveyed in the ACS include incarcerated persons, institutionalized⁹ persons, and the active duty military who are residing in the United States. The CCD and EDFacts data collections are administrative datasets that contain aggregated data for all U.S. public schools, local education agencies (LEAs), and SEAs.

As with all data collections, those used in this report are useful for calculating some types of estimates but poorly suited for calculating other types. For example, CPS data do not provide information about military personnel or individuals residing in institutionalized group quarters, such as prison inmates or patients in long-term medical or custodial facilities. Data from CPS cannot produce estimates below regional levels of geography for the age groups used in this report. ACS data are not available for long-term trend analyses, but include individuals living in a wider range of living quarters than the CPS data. Data from the CCD are appropriate for studying public school students in a given year, but do not provide information on private school students or young people who did not attend school in the United States. Datasets that track individual student records over time can provide more detailed information on the processes and precise timelines associated with completing high school or dropping out.¹⁰

The CPS and ACS data are limited in terms of their ability to identify alternative credential holders. Therefore, alternative credential recipients are not included in dropout counts and are not separated from regular diploma holders in the status completion rates.

Table A summarizes the different rates reported in this compendium.

Table A. Summary table of high school dropout, completion, and graduation rates

Standard Errors

Comparisons of estimates from sample surveys such as the CPS and ACS require consideration of several factors before they become meaningful. When using data from a sample, some margin of error will always be present in estimations of characteristics of the total population or subpopulation because the data are available from only a portion of the total population. Consequently, data from samples can provide only an approximation of the true or actual value. The margin of error of an estimate, or the range of potential true or actual values, depends on several factors such as the amount of variation in the responses, the size and representativeness of the sample, and the size of the subgroup for which the estimate is computed. The magnitude of this margin of error is measured by what statisticians call the “standard error” of an estimate.

When data from sample surveys are reported, a standard error is calculated for each estimate. The standard errors for all estimated totals, means, or percentages are reported in the reference tables.

In order to caution the reader when interpreting findings in the indicators, estimates from sample surveys are flagged with a “!” when the coefficient of variation (the standard error expressed as a percentage of the estimate) is between 30 and 50 percent, and suppressed with a “‡” when the coefficient of variation is 50 percent or greater or there are too few cases for a reliable estimate.

Data Analysis and Interpretation

When estimates are from a sample, caution is warranted when drawing conclusions about one estimate in comparison to another, or about whether a time series of estimates is increasing, decreasing, or staying the same. Although one estimate may appear to be larger than another, a statistical test may find that the apparent difference between them is not reliably measurable due to the uncertainty around the estimates. In this case, the estimates will be described as having no measurable difference, meaning that the difference between them is not statistically significant.

Whether differences in means or percentages¹¹ are statistically significant can be determined using the standard errors of the estimates. In these indicators and other reports produced by NCES, when differences are statistically significant, the probability that the difference occurred by chance is less than 5 percent, according to NCES standards.

For all indicators that report estimates based on samples, differences between estimates (including increases and decreases) are stated only when they are statistically significant. To determine whether differences reported are statistically significant, two-tailed t tests at the .05 level are typically used. In this report, the t test formula is not adjusted for multiple comparisons. When the variables to be tested are postulated to form a trend, the relationship is tested using linear regression. For more information on data analysis, please see the NCES Statistical Standards, Standard 5-1, available at https://nces.ed.gov/statprog/2012/pdf/Chapter5.pdf.

A number of considerations influence the ultimate selection of the data years to feature in the indicators. To make analyses as timely as possible, the latest year of available data is shown. The choice of comparison years is often also based on the desire to show the earliest available survey year. In the case of surveys with long time frames, such as the CPS, the beginning year of the indicator is set to 1977 to provide a 40-year trend line. In the figures and tables of the indicators, intervening years are selected in increments in order to show the general trend. The narrative for the indicators typically compares the most current year’s data with those from the initial year and then with those from a more recent period. Where applicable, the narrative may also note years in which the data begin to diverge from previous trends.

Data presented in the indicators do not investigate more complex hypotheses, account for interrelationships among variables, or support causal inferences. We encourage readers who are interested in more complex questions and in-depth analyses to explore other NCES resources, including publications, online data tools, and public- and restricted-use datasets at https://nces.ed.gov.

Symbols

In accordance with the NCES Statistical Standards, many tables in this volume use a series of symbols to alert the reader to special statistical notes. These symbols, and their meanings, are as follows:

— Not available.
† Not applicable.
# Rounds to zero.
! Interpret data with caution. The coefficient of variation (CV) for this estimate is between 30 and 50 percent.
‡ Reporting standards not met. Either there are too few cases for a reliable estimate or the coefficient of variation (CV) for this estimate is 50 percent or greater.

¹ See Digest of Education Statistics 2018, table 502.30.
² See Digest of Education Statistics 2018, table 501.80.
³ See discussion in Indicator 2 for more details.
⁴ Levin and Belfield estimate costs at $209,000 as of 2004. The estimate here is adjusted for inflation between March 2004 and March 2017 using March 2004 and March 2017 consumer price index adjustments.
⁵ CCD event dropout rates for 2011–12 and prior years can be accessed through reports available at https://nces.ed.gov/ccd/pub_dropouts.asp.
⁶ The status completion rate is not the inverse of the status dropout rate (i.e., the status completion rate does not equal 100 minus the status dropout rate). The rates are based on different age ranges, and whereas the status completion rate excludes high school students from its denominator, the status dropout rate includes high school students in its denominator.
⁷ Seastrom et al. (2006a) refer to this rate as the “Current Population Survey High School Completion Indicator.”
⁸ The AFGR indicator in this edition of the report is a repeat of the AFGR indicator in the previous edition since more recent data were unavailable.
⁹ IInstitutionalized includes those in correctional institutions or nursing homes. Members of the military living in nonfamily housing such as military barracks or aboard ship are included in the noninstitutionalized population.
¹⁰ Many states have student-level administrative record systems that follow student progress over time; these systems can be used for this kind of analysis. NCES is supporting the development of similar systems across additional states (see https://nces.ed.gov/programs/slds for details) and periodically conducts national-level longitudinal studies of high school students that can be used for such analysis (e.g., the High School Longitudinal Study of 2009).
¹¹ Throughout this report percentages are based on unrounded counts.

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