An Examination of Tuition Revenue Dependence as a Predictor of Master’s Program and Degree Completion Growth in the United States

Principal Investigator(s):  View help for Principal Investigator(s) Joseph H. Paris, Delaware Valley University; Jay R. Stefanelli, Rutgers University–New Brunswick

Version:  View help for Version V2

Name File Type Size Last Modified
Tuition Revenue Dependence - RQ1.xlsx application/vnd.openxmlformats-officedocument.spreadsheetml.sheet 274.5 KB 05/29/2025 11:47:AM
Tuition Revenue Dependence - RQ2.xlsx application/vnd.openxmlformats-officedocument.spreadsheetml.sheet 283.2 KB 05/22/2025 05:08:PM

Project Citation: 

Paris, Joseph H., and Stefanelli, Jay R. An Examination of Tuition Revenue Dependence as a Predictor of Master’s Program and Degree Completion Growth in the United States. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2025-05-29. https://doi.org/10.3886/E210881V2

Project Description

Summary:  View help for Summary Since the 1970s, master’s degrees represent the fastest growing degree in the United States (U.S.). Accordingly, there is a need for greater understanding of the factors that have contributed to this sustained, upward trend. Guided by resource dependence theory, we conducted hierarchical multiple linear regression analyses to examine whether more than 1,000 non-profit U.S. institutions’ dependence on tuition revenue (i.e., tuition revenue as a percentage of core revenues) is a statistically significant predictor of the percentage change in the number of master’s degree programs offered and master’s degree completions between 2005 and 2023. We found that tuition revenue does not make a statistically significant contribution to the prediction of master’s programs offered and master’s program completions. However, we found that Baccalaureate Colleges and institutions with higher student-to-faculty ratios (i.e., fewer faculty resources) were significantly more likely to experience increases in master’s program offerings and completions, demonstrating that institutional adaptation to financial pressures is complex and shaped by more than tuition revenue generation alone. We conclude by discussing the implications for institutional decision-making, importance of aligning the supply and demand for master’s degrees, and directions for future research.

Scope of Project

Subject Terms:  View help for Subject Terms IPEDS
Geographic Coverage:  View help for Geographic Coverage United States
Time Period(s):  View help for Time Period(s) 2005 – 2023 (IPEDS Reporting Years 2005 through 2023)
Collection Date(s):  View help for Collection Date(s) 4/2025 – 4/2025 (April 2025)
Universe:  View help for Universe Public and private non-profit institutions with a 2005 Basic Carnegie Classification of Baccalaureate Colleges (Arts & Sciences, Diverse Fields), Master’s Colleges and Universities (larger, medium, and smaller programs), Doctoral/Research Universities, and Research Universities (high research activity, very high research activity).
Data Type(s):  View help for Data Type(s) aggregate data

Methodology

Sampling:  View help for Sampling Our sample includes public and private non-profit institutions in the U.S. with a 2005 Basic Carnegie Classification of Baccalaureate Colleges (Arts & Sciences, Diverse Fields), Master’s Colleges and Universities (larger, medium, and smaller programs), Doctoral/Research Universities, and Research Universities (high research activity, very high research activity). These inclusion criteria resulted in our initial sample of 1,513 institutions. We excluded 37 institutions (2.4%) located in U.S. Territories. Using listwise deletion, we removed 103 institutions (6.8%) for missing tuition revenue data and four military academies (0.3%) that reported 0% of core revenues from tuition and fees.. We removed 101 institutions (6.7%) for reporting zero graduate student enrollments during the years of our data panel (2005-2023). We removed 17 institutions (1.1%) for missing faculty resources data. For RQ1, we removed 192 institutions (12.7%) for missing Classification of Instructional Program (CIP) code data preventing us from determining the number of master’s degree programs offered. For RQ2, we removed 198 institutions (13.0%) with an undefined percentage change in the number of master’s degree completions given that these institutions reported zero master’s degrees completed in 2005. We reviewed box plots for each of our outcome variables to identify extreme univariate outliers. For RQ1, we removed four cases (0.3%) with percentage increases in the number of master’s programs that ranged from 2,500% to 5,500%. For RQ2, we removed three cases (0.2%) with percentage increases in the number of master’s degree completions that ranged from 10,850% to 20,788%. These procedures resulted in analytical samples of 1,055 institutions for RQ1 and 1,050 institutions for RQ2. Table 1 presents the characteristics of the institutions in our analytical samples.
Data Source:  View help for Data Source  Integrated Postsecondary Education Data System (IPEDS), National Center for Education Statistics (NCES), U.S. Department of Education

U.S. Bureau of Labor Statistics

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V2 [2025-05-29]

V1 [2024-11-12]

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