Another look at the demand for higher education: Measuring the price sensitivity of the decision to apply to college

Savoca, Elizabeth

doi:10.1016/0272-7757(90)90040-c

Cited by 63 publications

(52 citation statements)

References 6 publications

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“…She states that 'in the presence of afQimative action efforts the probability of admission may be higher for a nonwhite or a female student." (Savoca, 1990. p 125) Savoca (1990) estimated that controlling for the probability of applying, the price elasticity was twice as large as previous work.…”

Section: General College Enrollmentmentioning

confidence: 83%

“…(Savoca, 1990. p 125) Savoca (1990) estimated that controlling for the probability of applying, the price elasticity was twice as large as previous work. She estimated the elastici^ of applying was -0.26.…”

Section: General College Enrollmentmentioning

confidence: 83%

“…Fuller et al also estimated the impact of financial aid scholarships to be positive. Savoca (1990) examined the decision to ^ly to college with the NLS_72 data. She included male and white dummy variables to account for the presence of afBrmative action in the probabili^ of being admitted.…”

Section: General College Enrollmentmentioning

confidence: 99%

“…It also includes socioeconomic data such as gender, ethnid^, family income, home address and SAT score. As in Savoca (1990), Weiler included dummy variables for males and minorities.…”

Section: General College Enrollmentmentioning

confidence: 99%

“…Universities are not only concerned with the number of people enrolling, but also the composition of students on campus. Savoca (1990) noted that the presence of afOmiative action programs may increase the probability of minorities and females being admitted.…”

Section: Overview Of Datamentioning

confidence: 99%

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Individual and aggregate demand for higher education: the role of strategic scholarships

Wohlgemuth

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This manuscript has been reproduced from the microfilm master. UMI films the text direct^ fix>m the origmal or copy submitted. Thus, some thesis and dissertation copies are in typewriter fice; whfle others may be fiom any type of computer printer.The quality of this reprodaction is dependent upon the qnalityr of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photogrq)hs, print bleedthrough, substandard margins, and improper alignment can adversely affect reproduction.In the unlikdy event that the author did not send UMI a complete numuscript and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note will indicate the deletion.Oversize materials (e.g., maps, drawings, charts) are reproduced by sectioning the original, b^inning at the upper 1^-hand comer and continuing fi'om left to right in equal sections with small overiaps. Each original is also photographed in one exposure and is included in reduced form at the back of the book.

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Section: General College Enrollmentmentioning

confidence: 83%

Section: General College Enrollmentmentioning

confidence: 83%

Section: General College Enrollmentmentioning

confidence: 99%

“…It also includes socioeconomic data such as gender, ethnid^, family income, home address and SAT score. As in Savoca (1990), Weiler included dummy variables for males and minorities.…”

Section: General College Enrollmentmentioning

confidence: 99%

Section: Overview Of Datamentioning

confidence: 99%

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Individual and aggregate demand for higher education: the role of strategic scholarships

Wohlgemuth

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Methods and Techniques of Enrollment Forecasting

Brinkman¹,

McIntyre²

1997

New Drctns for Instit Rsrch

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Enrollment forecasters have much to consider. A combination of quantitative and qualitative methods can sometimes be the best approach. Methods and Techniques of Enrollment Forecasting Paul T. Brinkman, Chuck McIntyreInstitutional researchers are often called on to conduct or assist with enrollment forecasts. Occasionally, personnel in institutional-planning offices, in state agencies, or in the marketing offices of continuing education divisions will be called on to produce such forecasts. Enrollment forecasts are fundamental elements of planning and budgeting at any higher education institution that depends on student enrollments or at any agency or organization that has responsibilities for supporting those institutions. Numerous institutional policy issues are related to enrollment forecasts-tuition policy, budget forecasting, faculty staffing, institutional closure or consolidation, and optimizing objectives related to the size and composition of enrollment (Weiler, 1987a).There is no one right way to forecast enrollment. In this chapter, we discuss a variety of approaches and associated issues. We relate choices of method or technique to specific circumstances and situations in an effort to provide some guidance to readers in choosing their own approaches. We focus on forecasting institutional enrollments. Factors Affecting EnrollmentNo one factor determines enrollments at a college or university. For the economist, enrollment will be determined by the intersection of measured supplyand-demand curves. For the demographer, enrollments are related to numbers of people and where they are located. For the higher education administrator, enrollment is determined by the combined effects of many manageable and unmanageable factors, categories that are roughly, though not completely, equivalent to supply and demand. In addition, there is always the possibility that a

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The Impact of College Sports Success on the Quantity and Quality of Student Applications

Pope

2009

Southern Economic Journal

150

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Empirical studies have produced mixed results on the relationship between a school's sports success and the quantity and quality of students that apply to the school. This study uses two unique data sets to shed additional light on the indirect benefits that sports success provides to NCAA Division I schools. Key findings include the following: (1) football and basketball success significantly increases the quantity of applications to a school, with estimates ranging from 2% to 8% for the top 20 football schools and the top 16 basketball schools each year, (2) private schools see increases in application rates after sports success that are two to four times higher than public schools, (3) the extra applications received are composed of both low and high SAT scoring students, thus providing potential for schools to improve their admission outcomes, and (4) schools appear to exploit these increases in applications by improving both the number and the quality of incoming students.

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Another look at the demand for higher education: Measuring the price sensitivity of the decision to apply to college

Cited by 63 publications

References 6 publications

Individual and aggregate demand for higher education: the role of strategic scholarships

Individual and aggregate demand for higher education: the role of strategic scholarships

Methods and Techniques of Enrollment Forecasting

The Impact of College Sports Success on the Quantity and Quality of Student Applications

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