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Exploring Carnegie’s New 3-Framework System – 2025 Student Access and Earnings (Part 2)

ByBlake Decker

In our previous blog post, we introduced the new 2025 Carnegie Classification system. Since its inception in 1973, the Carnegie Classification system has primarily relied on its Basic Classification framework that served as an overarching designation for institutions of higher education. The new 2025 Carnegie vintage expands the single Basic Classification into three separate classifications: Institutional Classification, Research Activities Designation, and Student Access and Earnings Classification. While our last post addressed the first two frameworks, this blog entry will cover the Student Access and Earnings Classification (SAEC) component. Because these are new constructs to many higher education leaders, we include more background information about these metrics than is typical in most blog posts.

an overview of Student access and earnings metrics

At its core, the Student Access and Earnings Classification (SAEC) “examines the extent to which an institution is enrolling undergraduate students who reflect the communities that the school serves and whether those students go on to earn competitive wages compared to similar people in their area” (SAEC Technical Manual). The following definitions are essential to understanding how the Access and Earnings Measures were calculated:

  • Access Measure: The Access Measure evaluates whether institutions are enrolling a student population that is representative of the locations they serve. Enrollment of undergraduate students by Pell grant status and underrepresented race/ethnicity were used to determine student population values. The institution-level data were then contextualized by comparing those data to location-based variables for the general population within each institution’s region of service (Carnegie Classification).
  • Earnings Measure: Economic outcomes were measured by comparing median post-attendance earnings as reported by the College Scorecard to earnings of people ages 22-40 who hold a high school diploma or higher in an institution’s region. Recognizing that student data are variable based on context, earnings data were analyzed based on the geographical and racial/ethnic composition of the student body (Carnegie Classification).

The initial view of the visualization below shows data for the 35 public universities in Texas, as additional checkbox filters are available to include private (in Texas) and out-of-state institutions. The scatterplot shows the combination of Access Measure (x-axis) and Earnings Measure (y-axis) scores for each university. The vertical and horizontal lines represent the cut points for institutions to be classified in one of the six combinations of Access and Earnings categories used in the new SAEC framework. For the Access Measure, institutions with a score greater than 1.0 are considered “Higher Access” while institutions below 1.0 are considered “Lower Access.” On the y-axis, there are three categories for the Earnings Measure: “Lower Earnings” is below 1.0, “Medium Earnings” is between 1.0 and 1.5, and “Higher Earnings” is above 1.5. The discussion below the scatterplot unpacks how the SAEC measures were calculated.

Note About Interpretation: For both the Access and Earnings measures, a score above 1.0 indicates that the institution had a higher value than the geography-based comparison group, while a score below 1.0 means the institution had a value lower than the comparison group. A score of 1.0 shows the institution and comparison group are the same on that particular metric.

understanding the saec methodology

Without getting too deep into the weeds on the methodology used for the SAEC measures, both the Access and Earnings measures are based on a ratio-of-ratios to determine an institution’s score values. In order to understand how these measures were calculated, we will walk through Texas A&M International University’s (TAMIU) data (identified in the visualization above) as an example.

The Access Measure is comprised of two components: Pell grant status and underrepresented minority (URM) student population.

  • For the Pell grant portion of the Access Measure, the public data file provided by Carnegie showed that 68.4% of TAMIU’s student body received Pell grants in 2023. The SAEC methodology then compared TAMIU’s Pell award rate to the “percentage of families with children earning less than 200% of federal poverty guidelines” (Carnegie Classification) across an enrollment-weighted combination of region, state, and national data. For TAMIU, this general population poverty rate was 47.5%. Once the data pieces were determined, the SAEC’s ratio-of-ratios methodology divided TAMIU’s 68.4% Pell award rate by the comparison group’s poverty rate of 47.5%. The resulting ratio of 1.44 (68.4%/47.5%) means that TAMIU’s student population had 44-percent more students from low-socioeconomic backgrounds than the general population to which TAMIU was being compared.
  • The second component of the Access Measure was a comparison of each institutions’ percentage of underrepresented minority (URM) students to the racial/ethnic composition of the population 25 or older with a high school diploma or higher across the same combination of geographies as described in the Pell grant example above. In the Carnegie data, the URM percentage was calculated by summing the percentage of students whose race/ethnicity was reported as either American Indian/Alaska Native, Black or African American, Hispanic or Latino, Native Hawaiian or Other Pacific Islander, or Two or More Races. For TAMIU, the Carnegie data file showed TAMIU’s URM rate was 97.4% in 2023, while the geographic comparison group was 95.5%, giving TAMIU a URM ratio of 1.02.
  • To calculate the overall Access Measure, the average of TAMIU’s Pell ratio (1.44) and URM ratio (1.02) was taken, resulting in an Access Measure value of 1.23.

A similar methodology was used for the Earnings Measure. The institutional metric was the “8-year post-entry median earnings” for a pooled cohort of students who entered the institution from 2011-12 and 2012-13, with those earnings compared to median earnings for the geography-based comparison group (Carnegie Classification). For TAMIU, the 8-year median earnings value reported by Carnegie was $43,366, while the comparison group’s median earnings was $24,469. Dividing TAMIU’s earnings by the comparison group earnings resulted in an Earnings Measure of 1.77 for TAMIU in the Carnegie data file, meaning that TAMIU’s median earnings were 77% above the enrollment-weighted average of the median earnings for their comparison group.

general observations about saec designations

  • The highest SAEC designation for institutions is “Opportunity Colleges and Universities – Higher Access, Higher Earnings.” The Opportunity Colleges and Universities designation is awarded to those institutions that have an Access Measure score of at least 1.0 and an Earnings Measure score of at least 1.5 for bachelor’s and higher institutions or 1.25 for primarily associate colleges.
  • Out of the more than 3,000 institutions that received an SAEC classification, 479 (16%) were deemed “Opportunity Colleges and Universities.” Across the 179 Texas institutions (public and private, 2-year and 4-year) with an SAEC classification, 35 (20%) institutions received this highest designation for Access and Earnings.
  • Public universities in Texas accounted for more than one-third (12) of the Texas institutions receiving the “Opportunity Colleges and Universities” designation. Within the A&M System, Texas A&M University-Kingsville (and presumably soon to be A&M System member University of Houston-Victoria) joined TAMIU as being named one of the “Opportunity Colleges and Universities” in Texas.
  • All 35 public universities in Texas were classified as either “Medium Earnings” or “Higher Earnings” in the 2025 SAEC designations.
  • Overall, almost 75% (26 of 35) of Texas public universities were rated as “Higher Access” and either “Medium Earnings” or “Higher Earnings.”

So What?

As we have previously discussed, the release of the 2025 Carnegie Classifications 3-framework system served as the biggest re-visioning of Carnegie since its inception more than 50 years ago. Central to this updated approach to classifying institutions of higher education was the introduction of the Student Access and Earnings Classification schema. This blog post has served as an initial introduction to the methodology and findings related to the initial release of the SAEC framework that is likely to generate additional discussions moving forward.

One of the key features of the methodology that is intriguing is how Carnegie accounted for the regionality of institutions in determining the geography-based comparison groups for the Access and Earnings measures. For most of the universities nationally in the 2025 Carnegie data, state-level metrics were used in calculating the enrollment-weighted averages for the comparison groups. However, for universities identified as Regional Public Universities (RPUs) by the Alliance for Research on Regional Colleges, more granular data for the Core-based Statistical Area (CBSA) were used in lieu of statewide data. This shift in methodology for RPUs provides for more nuanced, contextualized comparisons for institutions where the local context may be dramatically different from the overall statewide data, which is certainly the case for many public institutions in Texas. We will begin exploring data related to Regional Public Universities, including observations related to the 2025 Carnegie Classification framework, in our next blog post.