Effects of social and economic factors on four-year higher-education enrollments in Virginia

Strickland, Deborah C.; Bonomo, Vittorio; McLaughlin, Gerald W.; Montgomery, James R.; Mahan, Beatrice T.

doi:10.1007/bf00992034

Cited by 12 publications

(5 citation statements)

References 9 publications

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“…One of the challenges is identifying an appropriate measure of demand for higher education. Earlier work tends to focus on actual enrollment or enrollment relative to total pool of potentially eligible students (Strickland et al, 1984). The enrollment is modeled as a linear function of several explanatory variables, which were obtained by aggregating individual students, recorded from across each group.…”

Section: Methodsmentioning

confidence: 99%

Determinants of Aggregate Demand for and Supply of Higher Education in India

Rani¹,

Jegan²

2022

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The present paper specifies system of demand and supply equations for enrolment in higher education. GER and log enrollment are dependent variables, covering from 1980-81 to 2018-19 and estimated with OLS and 2SLS. GER models perform better than log of enrolment models in both the cases. GER models indicate positive relationship with income per capita while negative relationship with poverty and literate population with both OLS and 2SLS. Regarding the supply equations, none of the included variables are found to be statistically significant though exhibit expected relationship. Reported negative ratio of boys to girls indicate gender disparity, raising concerns. The paper concludes with policy implications and suggested areas for future research.

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Section: Methodsmentioning

confidence: 99%

Determinants of Aggregate Demand for and Supply of Higher Education in India

Rani¹,

Jegan²

2022

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“…Frances (1989) and Jordan (1992) provide critiques of an overdependence on demographic projections as the basis for forecasting enrollments, especially at the state level. Strickland and others (1984) use both social and economic factors in estimating enrollment demand for a statewide system. Bingham (1993) demonstrates how enrollment forecasting might be done within the framework provided by marketing theory.…”

Section: Alternative Methodologies For Enrollment Forecastingmentioning

confidence: 99%

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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“…Freshmen enrollment changed in ahnost direct proportion to the changes in high school graduates (elasticity 1.08). Lehr and Newton also found ttiat the unemployment rate and the size of the aimed forces had positive effects on freshmen enrollment Strickland, Bonomo, Mclaughlin, Montgomery, and Mahan (1984) examined 1980 enrollment for the state of Virginia. The goal of their research was to explain the ratio of enrollment (enroUment over high school graduates) by geogr^hic area (county and city level analysis).…”

Section: State Enrollment Stodiesmentioning

confidence: 96%

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

Wohlgemuth

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This is to certify that the Doctoral dissertation of Darin Ray Wohlgemuth has met the dissertation requirements of Iowa State University Committee Member CommitteetMember Committee Member Committee Member Committee Me^ Major Prof^^or the Major Pr^ram For the Graduate College Signature was redacted for privacy. Signature was redacted for privacy. Signature was redacted for privacy. Signature was redacted for privacy. Signature was redacted for privacy. Signature was redacted for privacy. Signature was redacted for privacy.

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Effects of social and economic factors on four-year higher-education enrollments in Virginia

Cited by 12 publications

References 9 publications

Determinants of Aggregate Demand for and Supply of Higher Education in India

Determinants of Aggregate Demand for and Supply of Higher Education in India

Methods and Techniques of Enrollment Forecasting

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

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