Financial Distress in U.S. Oilfield Services: A Multi-Model Analysis with Oil Price Dynamics

Rio Budiman; Abdul Mukti Soma

doi:10.59261/inkubis.v8i3.261

Authors

Rio Budiman Universitas Telkom
Abdul Mukti Soma Universitas Telkom

DOI:

https://doi.org/10.59261/inkubis.v8i3.261

Keywords:

financial distress, oilfield services, profitability, prediction models, panel data analysis, oil price dynamics

Abstract

Background: The oilfield services sector operates in a cyclical environment characterized by volatile oil prices, capital-intensive operations, and fluctuating upstream investment. These conditions increase firms’ exposure to financial distress and emphasize the importance of reliable prediction models.

Objective: This study compares the classification performance of four financial distress prediction models and examines the determinants of financial distress among publicly listed U.S. oilfield services firms.

Methods: Panel data from ten publicly listed U.S. oilfield services firms during 2010–2023, consisting of 140 firm-year observations, were analyzed using the Altman Z″, Zmijewski, Grover, and Springate models. Model classification differences were examined using nonparametric tests, while binary logistic regression was applied to evaluate the effects of leverage, profitability, firm size, oil price, oil price volatility, and the moderating effect of oil price volatility.

Results: The results reveal significant differences among the four models, demonstrating that financial distress classification varies depending on the model applied. The Springate model identified the highest number of distressed observations. Profitability was found to have a significant negative effect on financial distress, while leverage, firm size, oil price, and oil price volatility had no significant direct effects. However, oil price volatility significantly moderated the relationship between leverage and financial distress.

Conclusion: Financial distress in the oilfield services industry is primarily associated with internal financial performance, particularly profitability, while external market uncertainty affects financial vulnerability indirectly through leverage conditions. This study contributes to financial distress research by integrating model comparisons and industry-specific determinants, providing practical insights for managers, investors, and creditors.

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