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A Statistical Model for Predicting Failure of Institutions of Higher Education Using Financial and Other Institutional Parameters.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	A Statistical Model for Predicting Failure of Institutions of Higher Education Using Financial and Other Institutional Parameters./
Author:	Evans, Glenda Maria.
Description:	1 online resource (146 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 79-09(E), Section: A.
Contained By:	Dissertation Abstracts International79-09A(E).
Subject:	Higher education. -
Online resource:	click for full text (PQDT)
ISBN:	9780355929256

A Statistical Model for Predicting Failure of Institutions of Higher Education Using Financial and Other Institutional Parameters.
Evans, Glenda Maria.

A Statistical Model for Predicting Failure of Institutions of Higher Education Using Financial and Other Institutional Parameters. - 1 online resource (146 pages)

Source: Dissertation Abstracts International, Volume: 79-09(E), Section: A.

Thesis (Ph.D.)--Hampton University, 2018.

Includes bibliographical references

The purpose of this study was to create a bankruptcy predictor for higher education institutions. After a review of existing research, a clear need for a failure prediction method was discovered. The existing methods used by colleges and universities were either created for different sectors of businesses or lacked the transparency needed to allow the administrators the ability to verify rankings that the universities received. In this study, two different predictor models were created. Both utilized log regression models created for that purpose. The first model, the higher education bankruptcy predictor financial model, mimicked the Altman Z-model and contained five financial ratios. The second model, the higher education bankruptcy predictor model, used a larger sample of variables including financial and academic variables and was solved using logit regression. Both models proved to be effective at classifying closed and sustaining universities/colleges.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355929256Subjects--Topical Terms:

1148448
Higher education.
Index Terms--Genre/Form:

554714
Electronic books.

A Statistical Model for Predicting Failure of Institutions of Higher Education Using Financial and Other Institutional Parameters.
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500 $a Source: Dissertation Abstracts International, Volume: 79-09(E), Section: A.
500 $a Adviser: Sharad K. Maheshwari.
502 $a Thesis (Ph.D.)--Hampton University, 2018.
504 $a Includes bibliographical references
520 $a The purpose of this study was to create a bankruptcy predictor for higher education institutions. After a review of existing research, a clear need for a failure prediction method was discovered. The existing methods used by colleges and universities were either created for different sectors of businesses or lacked the transparency needed to allow the administrators the ability to verify rankings that the universities received. In this study, two different predictor models were created. Both utilized log regression models created for that purpose. The first model, the higher education bankruptcy predictor financial model, mimicked the Altman Z-model and contained five financial ratios. The second model, the higher education bankruptcy predictor model, used a larger sample of variables including financial and academic variables and was solved using logit regression. Both models proved to be effective at classifying closed and sustaining universities/colleges.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
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650 4 $a Finance. $3 559073
650 4 $a Economics. $3 555568
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