On Altman's Failure/nonfailure Model: A Comparison of Discriminant, Logit, Nearest Neighbor and Neural Net Models*

By Banerjee, Debasish; Cronan, Timothy P. et al. | Journal of Business and Entrepreneurship, July 1994 | Go to article overview

On Altman's Failure/nonfailure Model: A Comparison of Discriminant, Logit, Nearest Neighbor and Neural Net Models*


Banerjee, Debasish, Cronan, Timothy P., Jones, Thomas W., Journal of Business and Entrepreneurship


ABSTRACT

The underlying premise in most failure studies is that there exists a group of accounting and financial ratios of firms which distinguishes failed firms from nonfailed firms. Ex post facto classification analysis of OTC market data one year, two years, three years, and four years prior to failure was used. Models incorporating Altman's variables were developed using three statistical procedures-discriminant, logit, and nearest neighbor-and an artificial neural network. Results indicate that the statistical models have low predictive power as compared with the artificial neural network model.

INTRODUCTION

In the present economy of the United States, small businesses play a very influential role. They greatly outnumber large business firms. Whereas a large number of small businesses enter the economy each year, many leave the market place either by way of failure or by mergers and acquisitions. The sheer number of small businesses functioning in the economy stimulates attention as to their functionality; and, more so, does their failure. Accordingly, in the last two decades, considerable interest has been shown by researchers trying to develop mathematical models for predicting business failure.

It has been indicated by Beaver, Kennelly, and Vass (1968) that accounting data have predictive ability which could be used for several purposes; for example, prediction of financial performance and accounting earnings (Kinney, 1971; Lawson, 1971; Patell, 1976; Chen & Shimerda, 1981), predicting security market behavior (Brown & Niederhoffer, 1968; Foster, 1973; Lev, 1979; Kross & Schroeder, 1984), and predicting business failure (Beaver, 1967,1968; Airman, 1968,1971,1973; Airman & Spivack, 1983). Most of this research has dealt with firms in general, without devoting specific attention to small business. Researchers have used financial and accounting ratios to develop models used for purposes of predicitng business failures. A more recent paper (Jones, Cronan, & Stettler, 1988) developed several classification models for data two years prior to failure for OTC firms. Their models exhibited only modest predictive ability; however, they did not investigate the ability of Altaian's widely cited variables (Airman, 1968) to predict failure/nonfailure.

RESEARCH METHODOLOGY

Research Objective

The purpose of this study was to develop a model which incorporates Airman's variables (Airman, 1968) to discriminate failed and nonfailed firms in the OTC market.1 Directly related to this objective is the sensitivity of the classification rates to the procedure employed and, of course, the external validity of these variables to a population different from that considered by Airman2.

Sample Selection

A paired sample design matching each failed firm with a nonfailed firm was used in the study. Firms were matched according to Moody's Industrial Classification and total asset size with the additional requirements that the paired firms existed during the same time frame and published complete financial data. Lacking a comprehensive list of failed firms, identification of the sample of these firms was verified through several sources-articles in professional journals, news reporting magazines, and Moody's OTC Industrial Manual.

After the failed firms were selected and grouped according to Moody's Industrial Classification, the nonfailed firms (for which complete financial data were available) were selected that had the closest total asset sizes during the same time frame.3 Data up to four years prior to failure for 176 firms during the time period 1967-1983 were collected.

Variable Selection

Since a focus of the present study was to investigate the external validity of Airman's variables, a variable selection technique was not utilized to identify a set of "best" predictor variables. The variables used in the model, except for one surrogate, were those suggested by Airman (Airman, 1968). …

The rest of this article is only available to active members of Questia

Sign up now for a free, 1-day trial and receive full access to:

  • Questia's entire collection
  • Automatic bibliography creation
  • More helpful research tools like notes, citations, and highlights
  • Ad-free environment

Already a member? Log in now.

Notes for this article

Add a new note
If you are trying to select text to create highlights or citations, remember that you must now click or tap on the first word, and then click or tap on the last word.
One moment ...
Default project is now your active project.
Project items

Items saved from this article

This article has been saved
Highlights (0)
Some of your highlights are legacy items.

Highlights saved before July 30, 2012 will not be displayed on their respective source pages.

You can easily re-create the highlights by opening the book page or article, selecting the text, and clicking “Highlight.”

Citations (0)
Some of your citations are legacy items.

Any citation created before July 30, 2012 will labeled as a “Cited page.” New citations will be saved as cited passages, pages or articles.

We also added the ability to view new citations from your projects or the book or article where you created them.

Notes (0)
Bookmarks (0)

You have no saved items from this article

Project items include:
  • Saved book/article
  • Highlights
  • Quotes/citations
  • Notes
  • Bookmarks
Notes
Cite this article

Cited article

Style
Citations are available only to our active members.
Sign up now to cite pages or passages in MLA, APA and Chicago citation styles.

(Einhorn, 1992, p. 25)

(Einhorn 25)

1

1. Lois J. Einhorn, Abraham Lincoln, the Orator: Penetrating the Lincoln Legend (Westport, CT: Greenwood Press, 1992), 25, http://www.questia.com/read/27419298.

Cited article

On Altman's Failure/nonfailure Model: A Comparison of Discriminant, Logit, Nearest Neighbor and Neural Net Models*
Settings

Settings

Typeface
Text size Smaller Larger Reset View mode
Search within

Search within this article

Look up

Look up a word

  • Dictionary
  • Thesaurus
Please submit a word or phrase above.
Print this page

Print this page

Why can't I print more than one page at a time?

Full screen

matching results for page

Cited passage

Style
Citations are available only to our active members.
Sign up now to cite pages or passages in MLA, APA and Chicago citation styles.

"Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences." (Einhorn, 1992, p. 25).

"Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences." (Einhorn 25)

"Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences."1

1. Lois J. Einhorn, Abraham Lincoln, the Orator: Penetrating the Lincoln Legend (Westport, CT: Greenwood Press, 1992), 25, http://www.questia.com/read/27419298.

Cited passage

Welcome to the new Questia Reader

The Questia Reader has been updated to provide you with an even better online reading experience.  It is now 100% Responsive, which means you can read our books and articles on any sized device you wish.  All of your favorite tools like notes, highlights, and citations are still here, but the way you select text has been updated to be easier to use, especially on touchscreen devices.  Here's how:

1. Click or tap the first word you want to select.
2. Click or tap the last word you want to select.

OK, got it!

Thanks for trying Questia!

Please continue trying out our research tools, but please note, full functionality is available only to our active members.

Your work will be lost once you leave this Web page.

For full access in an ad-free environment, sign up now for a FREE, 1-day trial.

Already a member? Log in now.