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Examining financial and non-financia...

Lee, Richard A.

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Examining financial and non-financial indicators for predicting private higher education viability.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Examining financial and non-financial indicators for predicting private higher education viability./
Author:	Lee, Richard A.
Description:	209 p.
Notes:	Adviser: Richard Yellen.
Contained By:	Dissertation Abstracts International69-01A.
Subject:	Education, Finance. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3299652
ISBN:	9780549436737

Examining financial and non-financial indicators for predicting private higher education viability.
Lee, Richard A.

Examining financial and non-financial indicators for predicting private higher education viability. - 209 p.

Adviser: Richard Yellen.

Thesis (Ph.D.)--Northcentral University, 2008.

Administrators of private institutions of higher education rely on the ability of ratios to assess financial viability. Numerous publications now exist to assist financial analysts in understanding an institution's unique financial condition; however, most administrators lack the resources or the time to decipher the data. Instead, strategic financial and nonfinancial ratios allow administrators to focus on those measures considered critical to the institution. Each of these indicators can vary depending on the institution's size, control, location, history, mission, or specific goals. Determining a unique set of indicators comparable across peer institutions can be a challenging task. A total of 766 private colleges and universities listed by Moody's Municipal Financial Ratio Database, Guidestar.org and the Integrated Postsecondary Educational Database (IPEDS) were used in the study. The Consolidated Financial Index (CFIRTM) developed by KPMG LLP, Prager, Sealy & Co., LLC, and Bearing Point, Inc. was then utilized to classify institutions as either financially strong or weak. Discriminant analysis and logistic regression tests were then used to analyze whether student demographics, demand, capitalization, capital spending, endowments, college affordability, revenue contribution and tuition subsidy ratios discriminated between the two CFI classifications, strong or weak. The results of the study indicated that several ratios provide discriminating capabilities including capitalization rates, capital spending, endowments, tuition subsidies and revenue contribution ratios.

ISBN: 9780549436737Subjects--Topical Terms:

1020300
Education, Finance.

Examining financial and non-financial indicators for predicting private higher education viability.
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245 1 0 $a Examining financial and non-financial indicators for predicting private higher education viability.
300 $a 209 p.
500 $a Adviser: Richard Yellen.
500 $a Source: Dissertation Abstracts International, Volume: 69-01, Section: A, page: 0121.
502 $a Thesis (Ph.D.)--Northcentral University, 2008.
520 $a Administrators of private institutions of higher education rely on the ability of ratios to assess financial viability. Numerous publications now exist to assist financial analysts in understanding an institution's unique financial condition; however, most administrators lack the resources or the time to decipher the data. Instead, strategic financial and nonfinancial ratios allow administrators to focus on those measures considered critical to the institution. Each of these indicators can vary depending on the institution's size, control, location, history, mission, or specific goals. Determining a unique set of indicators comparable across peer institutions can be a challenging task. A total of 766 private colleges and universities listed by Moody's Municipal Financial Ratio Database, Guidestar.org and the Integrated Postsecondary Educational Database (IPEDS) were used in the study. The Consolidated Financial Index (CFIRTM) developed by KPMG LLP, Prager, Sealy & Co., LLC, and Bearing Point, Inc. was then utilized to classify institutions as either financially strong or weak. Discriminant analysis and logistic regression tests were then used to analyze whether student demographics, demand, capitalization, capital spending, endowments, college affordability, revenue contribution and tuition subsidy ratios discriminated between the two CFI classifications, strong or weak. The results of the study indicated that several ratios provide discriminating capabilities including capitalization rates, capital spending, endowments, tuition subsidies and revenue contribution ratios.
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