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States’ Potential Enrollment of Adult Students: A Stochastic Frontier Analysis

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Abstract

This study shows that financial aspects of state higher education policies, particularly tuition, have an impact on the level of enrollment of adult undergraduates within a state. This study also demonstrates how stochastic frontier analysis (SFA) can be utilized to examine the potential maximum enrollment of adult learners in postsecondary education and generate state-level scores that can be utilized to rank states according to the difference between the potential maximum and actual enrollment of adults in higher education.

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Notes

  1. More accurately, at point A, State2 may have achieved both technical and allocative efficiency. Allocative efficiency is the use inputs, at given input prices (the slope of the straight lines) that maximize tuition revenues and minimize costs or maximize profits (in the case of states with for-profit higher education institutions). Units that achieve both technical and allocative efficiency or where the slope of the straight line is equal to the slope of the curve (e.g., FTE2) are otherwise known as economically efficient. This study, however, addresses only technical efficiency.

  2. Additionally, compared to regression models that are estimated via OLS techniques, SFA models that are estimated via maximum likelihood (ML) techniques produce more efficient beta estimates and consistent variances.

  3. A time-variant version of the Battese–Coelli (Battese and Coelli 1995) parametization of SFA was estimated but did not indicate that inefficiency changed over the sample period.

  4. Although not shown, because the dependent variable in Eq. 2 is defined in terms of technical inefficiency, the state-specific variable associated with a negative coefficient would have a positive effect on technical efficiency.

  5. A Bayesian SFA model would avoid the imposition of a specific form of density function of μ it in Eq. 2. The calibration of a Bayesian SFA model, however, would require numerical integrations via Monte Carlo methods and Importance Sampling, which is beyond the methodological scope of this study.

  6. Philosophically, the specific circumstances include the notion that members of society were in an original position where they agreed to a social contract that defined the basic rights and duties of its members and each member was guaranteed such rights. Additionally, economic and social inequities are structured so as to ensure that both are to the advantage of all members of society.

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Acknowledgments

This paper is based on a major revision of a paper presented November 2008 at the Association for the Study of Higher Education Conference in Jackson, Florida. This research was funded by Lumina Foundation for Education. The opinions expressed in this article are those of the authors and do not necessarily represent the views of Lumina Foundation. This paper benefited from the comments and suggestions of an anonymous reviewer.

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  1. Education Leadership, Higher Education, and International Education, University of Maryland, Benjamin 2200, College Park, MD, 20742, USA

    Marvin A. Titus

  2. Department of Higher Education, University of Virginia, Charlottesville, VA, USA

    Brian Pusser

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Titus, M.A., Pusser, B. States’ Potential Enrollment of Adult Students: A Stochastic Frontier Analysis. Res High Educ 52, 555–571 (2011). https://doi.org/10.1007/s11162-010-9211-2

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