Date of Publication

9-18-2021

Document Type

Bachelor's Thesis

Degree Name

Bachelor of Science in Applied Economics major in Financial Economics/ Bachelor of Science in Accountancy

Subject Categories

Economics | Finance

College

School of Economics

Department/Unit

Economics

Thesis Advisor

Angelo Unite
Anne Marie Go
Madaleine Estabillo

Defense Panel Chair

Angelo Unite

Defense Panel Member

Anne Marie Go
Madaleine Estabillo

Abstract/Summary

When a firm is unable to meet its financial obligations, it falls under the vulnerable state of financial distress. If left unaddressed, this may lead to the eventual bankruptcy of the firm. Thus, it is of great significance if investors and creditors can predict this state in order for them to prevent losses. This paper analyzes the significance, predictive accuracy, and the marginal effects of accounting, market, and macroeconomic variables in predicting financial distress using a logistic regression analysis for an unbalanced panel dataset consisting of 1,226 company-year observations of publicly listed industrial firms in the Philippines. We build a model using data from the firm’s financial statements, PSE monthly reports, and the Bangko Sentral ng Pilipinas. Our empirical results show that among all the variables, liquidity is the most significant and has the greatest impact in determining the probability of financial distress. Furthermore, we find that the consolidated model, which contains all the types of variables, yields the best fitting and most accurate model in predicting financial distress when compared to the nested models.

Abstract Format

html

Language

English

Format

Electronic

Physical Description

93 leaves

Keywords

Bankruptcy--Philippines; Business failures--Philippines

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Embargo Period

9-15-2023

Available for download on Friday, September 15, 2023

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