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Nonlinear relationships in bankruptcy prediction and their effect on the profitability of bankruptcy prediction models

Author

Listed:
  • Christian Lohmann

    (University of Wuppertal)

  • Steffen Möllenhoff

    (University of Wuppertal)

  • Thorsten Ohliger

    (parcIT GmbH)

Abstract

This study uses generalized additive models to identify and analyze nonlinear relationships between accounting-based and market-based independent variables and how these affect bankruptcy predictions. Specifically, it examines the independent variables that Altman (J Financ 23:589–609, 1968; Predicting financial distress of companies. Revisiting the Z-score and ZETA® models. Working paper, 2000) and Campbell et al. (J Financ 63:2899–2939, 2008) used and analyzes what specific form these nonlinear relationships take. Drawing on comprehensive data on listed U.S. companies, we show empirically that the bankruptcy prediction is influenced by statistically and economically relevant nonlinear relationships. Our results indicate that taking into account these nonlinear relationships improves significantly several statistical validity measures. We also use a validity measure that is based on the profitability of the bankruptcy prediction models in the context of credit scoring. The findings demonstrate that taking into account nonlinear relationships can substantially increase the discriminatory power of bankruptcy prediction models.

Suggested Citation

  • Christian Lohmann & Steffen Möllenhoff & Thorsten Ohliger, 2023. "Nonlinear relationships in bankruptcy prediction and their effect on the profitability of bankruptcy prediction models," Journal of Business Economics, Springer, vol. 93(9), pages 1661-1690, November.
    • Handle: RePEc:spr:jbecon:v:93:y:2023:i:9:d:10.1007_s11573-022-01130-8
    DOI: 10.1007/s11573-022-01130-8
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    More about this item

    Keywords

    Accounting-based information; Bankruptcy prediction; Profitability of credit scoring; Generalized additive model; Nonlinear relationships;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting

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