Modeling the relationship between leverage and firm performance: a threshold analysis using the PSTR model

Abstract

Purpose

The relationship between leverage and firm performance has been a subject of great interest to researchers, but the empirical findings are, at best, mixed. Against this background, we attempt to investigate this controversial issue by hypothesizing the nonlinearity of this relationship. Specifically, we aim to determine whether there exists an optimal threshold of firm size above which increasing levels of debt stop undermining (or start enhancing) firm performance.

Design/methodology/approach

Our study uses a nonlinear modeling specification, that is, the Panel Smooth Transition Regression (PSTR) model proposed by González et al. (2005). This model is a fixed-effects panel that accounts for cross-country heterogeneity and time variability, while also allowing for smooth transitions between a limited number of “extreme regimes.”

Findings

The study reveals a statistically significant negative relationship between leverage and firm performance for firms below size thresholds. But after exceeding these thresholds, firms can experience a substantial increase in accounting and financial performance.

Originality/value

The authors offer novel insights into the contingent role played by firm size on the capital structure–performance nexus. To our knowledge, few studies have delved into the threshold effects of leverage on firm performance. The threshold firm size level can be considered, therefore, as a benchmark for firms in optimizing their capital structure. From this perspective, small-sized firms are invited to prioritize internal financing to avoid the detrimental impact of depts on their performance. However, large-sized firms may find it advantageous to leverage external financing through debt in order to potentially enhance their performance.

Citation

Omri, N.A.-E., Neffati, N. and Guenichi, H. (2024), "Modeling the relationship between leverage and firm performance: a threshold analysis using the PSTR model", Managerial Finance, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/MF-07-2024-0500