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Article Excerpt
Abstract
This study was conducted to measure the impact of H-University's (HU's) tuition increases on enrollment. Based on an internal survey, this study attempts to explain the sensitivity of student enrollment to tuition variations. In addition, this paper develops an aggregate enrollment model and uses the common economic variables such as tuition, income, wage rates, financial aids, and unemployment rates to explain the sensitivity of demand. The most significant finding of this study is that tuition consideration seems to have a relatively small effect on students' decisions. Actually, enrollment at HU (a private institution) have increased despite higher tuition rate. Possible justifications could be proposed, such as the necessity of higher education and the fact that higher education is a continued investment in human capital, in which the more relevant decision factor is the corresponding expected rate of return and not just the cost of investment. (JEL D11, C13)
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Introduction
The study of tuition changes and the corresponding enrollment at different institutions of higher education is always beneficial to their financial planning. This would attract even more attention when, in absence of sufficient state and federal funds at times of economic recession and budget crunch, institutions of higher education may consider resorting to higher tuition. Although the findings should concern both public and private schools, private higher education institutions whose main source of funds is tuition may consider this study even more interesting.
This report was conducted to quantify the impact of the tuition increases (at HU, a private institution) on enrollment by randomly surveying applicants who have enrolled or not enrolled in the university. The subjects were students attending the extended campus (EC), a unit of H-University (HU). Results of the study indicate the following: Of those surveyed, 77.5 percent of the undergraduate and 67.1 percent of graduate students said that the major reason that students enrolled at HU was the specialty of aviation. Meanwhile, 70 percent of the non-attending undergraduate and 61.4 percent of graduate applicants indicated that the reason for not enrolling was not the lack of academic majors of their interest. In addition, the time series data for enrollment and its determinants have been examined for all four semesters, including Summer Sessions A and B, within the period of 1990-2000. The analysis and findings of the enrollment variable, which is specified as a function of tuition, income, wage rate, financial aid, and the unemployment rate, will be presented in this paper.
Review of the Literature
Given the phenomenal increases in tuition at both public and private universities during the 1980s and 1990s, a major concern has been whether access to public higher education has been affected [Heller, 1996]. The decision to enroll in a higher education institution may be seen as an investment versus a current consumption decision [Campbell and Siegel, 1967]. Most multivariate analyses examining the relationship between tuition and enrollment fall under two categories: cross-sectional and time-series studies. Cross-sectional studies examine individual student behavior in the face of various post secondary options while time-series studies analyze changes over time in aggregate student enrollment [Heller, 1996].
Campbell and Siegel [1967] attempted to use aggregate enrollment data to explain the movements of demand during the period 1919-64. They found that for a given population, demand for enrollment should be directly proportional to the expected monetary and real yields from education, income, and the consumer price index and inversely proportional to the nominal and real costs of education. The model used was a hybrid investment consumption model in which the results may not be used to separate out the contribution of each of these elements to the demand for higher education. The calculations made in this study exclude both graduate students and those enrolled in two-year institutions. Using enrollment ratio as a measure of the quantity demanded, the income and price elasticities were calculated to be +1.2 and -0.44, respectively. Although they were found to be statistically significant, the small sample size raises questions about the reliability of the elasticity coefficients'est imates.
Through an analysis of data for individual states from 1976-93, Heller [1996] addressed the relationship between tuition, financial aid, and access to public higher education in the U.S., in which financial aid acts as a price discount by lowering the net cost to enrollees. Therefore, its impact on the relationship between tuition and access to higher education is critical. First-time enrollees are found to be more price sensitive because of their lack of investment in a post-secondary education. This study also confirmed two relationships. First, at least among some groups, there was a positive association between levels of grant spending and enrollment rates. Second, the study confirmed a positive relationship between unemployment and enrollment.
Based on the time series data from 1964-91, Hsing and Chang [1996] have examined some of the determinants of enrollment at private colleges and universities. Enrollment is defined as a function of tuition and other costs, income, wage rate, and the unemployment rate. It was observed that higher unemployment rates bring more enrollments while higher wage rates cause enrollment to decline. The elasticities of enrollment with respect to tuition, income, wage rate, and the unemployment rate was estimated to be -0.254, 0.675, 0.577, and 0.041. Rising tuition elasticities were attributed to the rising tuition, along with other related costs such as a fraction of total income and the increasing number (and relatively lower cost) of available substitute services.
Jackson and Weathersby [1975] reviewed seven major empirical studies of student demand and compared their quantitative results. The following results are briefly discussed below. Hight [1970] postulated a four-equation supply and demand model to treat public and private schools separately but was unable to reach statistically significant results for all equations. The income elasticities for the public and private sectors were 0.977 and 1.701, respectively. Galper and Dunn [1969] re-analyzed their data to relate the inductions and discharges from the armed forces with four-year college enrollment and estimated the income elasticity of 0.69. Basing the demand estimates on a lifetime utility-maximization model for an individual, Hoenack [1967] offered separate demand functions for each campus of the University of California (UC). His proposed aggregate demand was a replication of the individual demand estimates. The study was based on Jackson's cross-sectional sample [1975]. Hoenack [1967] reported an average UC price elasticity of -0.85 and an income elasticity of 0.7. Hoenack, Weiler, and Orvis [1973] conducted a similar study for the University of Minnesota based on the longitudinal data from 1948-72. Tuition elasticity coefficients estimated for the four divisions varied from 0.533 to -1.811. They found that depending on the college, a $100 increase in tuition would reduce the enrollment by 2.62 to 0.12 percentage points.
In their study of student demand based on national and Massachusetts data, Corrazzini, Dugan, and Grabowski [1972] formulated an enrollment model for higher education with demand being subject to non-price rationing by academic admission standards. They found college attendance and socioeconomic status to have a strong structural relationship. The total enrollment rate was most...
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