Abstract
In this chapter, we focus on the behavior of colleges and universities in the markets for students. We begin by providing some background information on the pioneering work of economists on production, competition, and market structures. We then turn to the alternative goals and objectives that have been offered for postsecondary institutions. Unlike typical industries where the behavioral assumption is made that the organization is trying to maximize profits, postsecondary institutions have been described by economists as striving to maximize a range of things such as revenues, utility, prestige, or discretionary budgets. In the next section of the chapter we review the different structures that economists commonly use to describe product markets, and how postsecondary markets compare to these models. Following the discussion of market structures, we turn to the topic of competition in postsecondary education. Despite the impression that competition is something new to higher education, in fact colleges have a long history of competing with each other in ways that extend beyond athletics. In postsecondary education, colleges engage in price and non-price competition for students. The next topic that we cover is education production. Economists use a production function or model to describe how organizations convert inputs into outputs to work towards their goals. We believe that the production function analogy holds quite well for a number of reasons, and yet we will discuss some of the important differences in the production function between the typical for-profit sector and higher education that complicate the comparison. In the Extensions section, we discuss how online and distance education may affect the markets in which colleges and universities compete. Finally, in the Policy Focus section, we examine how states use funding formulas to distribute appropriations to public institutions and impact their behavior.
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Notes
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A. R. J. Turgot (1767) is largely credited with being the first to describe how a firm’s total output can be modeled as a function of inputs based on assumptions about the marginal productivity and cross-productivity of inputs. Malthus (1798) later extended this notion to a logarithmic relationship between inputs and output. Excellent reviews of the early economic literature on production can be found in Humphrey (1997) and Mishra (2007).
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Key pieces of antitrust legislation in the United States include the Sherman Act of 1890 and the Clayton Act of 1914.
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The marginal revenue curve will be linear and downward-sloping when the demand curve (i.e., the average revenue curve) is also linear and downward-sloping. Both are derived from the total revenue function. The relationships between total, marginal and average revenue functions can be readily defined mathematically as follows:
\( TR={\alpha}_1Q - {Q}^2 \)
\( MR=\partial TR/\partial Q={\alpha}_1-2Q \)
\( AR=TR/Q={\alpha}_1-Q \)
The U-shaped marginal cost curve follows from the assumption that there are economies and diseconomies of scale in the provision of services. However, the same basic results discussed here also hold for other situations where the marginal revenue and/or marginal cost curves have different shapes.
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See Bowen (1980) for more details.
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Other economists who assumed that the goal of postsecondary institutions is to maximize utility or prestige include James (1978, 1990) and Winston (1999). Epple, Romano, and Sieg (2006) posited that the goal of postsecondary institutions is to maximize the quality of experiences for students. For further discussion see Garvin (1980), James (1990), Winston (1999), and Melguizo and Strober (2007).
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Economists have also developed versions of oligopoly in which sellers produce heterogeneous goods and services (see Kuenne, 1992). However, the usual case is to consider a market with only a few large sellers whose products are viewed as being very similar to each other.
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See Becker and Toutkoushian (2013) for a more detailed discussion of these issues.
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The Herfindahl Index could be calculated on a 0–1 scale or a 0–10,000 scale depending on the units of measure for market shares. For example, a firm with a 5 % market share would have a value of 5 rather than 0.05. In this instance, the rescaled Herfindahl Index is bounded between 0 and 10,000.
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These statistics were obtained from Trends in College Pricing 2014. Washington, DC: The College Board.
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For example, in a recent study, Leeds and DesJardins (2015) found that The University of Iowa’s National Scholars Awards have successfully increased the probability of enrollment among high-ability non-resident students.
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See, for example, Pascarella and Terenzini (2005).
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The complete mission statement for the University of Georgia can be found at http://www.uga.edu/profile/mission/.
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The complete mission statement for the University of Iowa can be found at https://provost.uiowa.edu/ui-academic-mission.
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See, for example, Winston (1999).
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See, for example, Rothschild and White (1995).
- 31.
The Cobb-Douglas production function is most often attributed to the work of Paul Douglas and Charles Cobb in 1928. Among the appealing features of this production function are that it allows for increasing, decreasing, or constant returns to scale, and it exhibits diminishing marginal returns to scale for each factor of production. Interestingly, the production function developed by von Thunen in the mid nineteenth century is the same as the more widely-cited Cobb-Douglas function which was developed 65 years later in 1928. Humphrey (1997) shows the equivalence between von Thunen’s production function and the Cobb-Douglas production function. Other economists of note who developed versions of the Cobb-Douglas production function include Wicksteed (1894) and Wicksell (1893). Readers who are interested in more details on the development and use of the Cobb-Douglas production function are referred to Douglas (1976) and Filipe and Adams (2005).
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There are many different ways to classify states by the funding mechanisms that they use (Layzell & McKeown, 1992). According to a report produced by MGT of America, in 2006 there were 26 states using “funding formulas” driven by enrollments, 14 states using “benchmark or peer funding,” and 11 states using “performance funding”.
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The differences between the earlier interest of some states in performance funding—where a small portion of funding was based on performance measures—and the renewed, more expansive and widespread interest in performance funding have been referred to as PF 1.0 and PF 2.0, respectively (Dougherty & Reddy, 2013).
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Glossary
Glossary
Symbol | Definition |
|---|---|
TR | Total revenue |
Q | Quantity of output |
MR | Marginal revenue |
AR | Average revenue |
CR | Concentration ratio |
Rj | Revenues for the j-th largest firm in an industry |
HI | Herfindahl Index |
PR | Price for resident (in-state) students |
PNR | Price for non-resident (out-of-state) students |
QR | Quantity of resident students |
QNR | Quantity of non-resident students |
L | Quantity of labor |
K | Quantity of capital |
Zj | Production input of j-th type (labor, capital, raw materials) |
Ojk | Output of the j-th type for the k-th institution for performance funding models |
WOk | Weighted total outcomes for the k-th institution |
wjk | Priority weight for the j-th output and k-th institution |
sj | Scale weight for j-th output in performance funding models |
Gk | Total government funding for the k-th institution |
\( \overline{\mathrm{Y}} \) | Average faculty salary |
gk | Supplemental government funding for designated operations |
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Toutkoushian, R.K., Paulsen, M.B. (2016). Competition and Production in Higher Education. In: Economics of Higher Education. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-7506-9_8
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