Journal of Intelligent Strategic Management

Journal of Intelligent Strategic Management

Assessing the Nexus between Managerial Efficacy and Credit Facility Quality among Banks Listed on the Tehran Stock Exchange: A Quantile Regression Framework

Document Type : Original Article

Authors
1 PhD Candidate in Finance, specializing in Financial Engineering and Risk Management, Alborz Campus, University of Tehran, Tehran, Iran.
2 Professor, Department of Financial Engineering, Faculty of Management, University of Tehran, Tehran, Iran.
3 Professor, Department of Financial Markets and Institutions, Faculty of Management, University of Tehran, Tehran, Iran.
Abstract
Drawing upon rigorous empirical analyses and meticulous statistical estimations, the present study investigates the functional role of managerial competence in shaping the quality of extended credit facilities, contextualized within an environment replete with structural and behavioral heterogeneities. The preliminary phase involved ascertaining the optimal estimation framework through diagnostic specifications—namely, the Likelihood-Ratio (F-Limer) and Hausman tests—which corroborated the superiority of the fixed-effects panel data model. Nevertheless, given the inherent complexities and non-linear volatilities characterizing financial time-series data, the principal methodological thrust of this inquiry pivots toward quantile regression. The imperative for this methodological departure was rigorously substantiated via Slope Equality and Quantile Symmetry diagnostics, which unequivocally evinced the inadequacy of conventional linear paradigms in capturing the differential behavioral responses of banks across disparate risk strata, thereby underscoring the necessity to eschew oversimplified causal inferences. The quantitative findings, predicated upon descriptive statistics and robust diagnostic evaluations, evince pronounced skewness and significant kurtosis in the underlying variable distributions, which further accentuates the indispensability of the quantile regression framework alongside orthodox econometric techniques. In parallel, whereas the standard F-Limer and Hausman criteria espoused the fixed-effects configuration, the more advanced Slope Equality and Quantile Symmetry tests definitively corroborated the heterogeneous nature of the estimated coefficients across the entire distributional spectrum, unveiling multifarious behavioral architectures intrinsic to the banking system. The ultimate estimations derived from the quantile regression not only validate all stipulated research hypotheses but also delineate a distinctly nuanced and divergent portrayal of bank conduct at varying risk quantiles. Macro-prudential and structural determinants—such as GDP oscillations, inflationary trajectories, and sanction-induced exogenous shocks—alongside internal banking fundamentals, including capital adequacy ratios, profitability metrics, and bank size, manifest contradictory and non-monotonic influences across different quantiles, thereby robustly affirming the non-linear essence of these interrelationships.
A pivotal revelation of this study is the substantiation of the asymmetric role of managerial ability; specifically, within highly distressed banking entities (i.e., the 0.9 quantile), this variable paradoxically transforms into a decisive and counter-cyclical instrument for curbing non-performing loan ratios—a phenomenon distinctly absent at lower risk thresholds. This comprehensive empirical evidence, while meticulously explicating the prevailing mechanisms governing credit facility quality, strongly intimates that banking policy frameworks must be meticulously calibrated to each bank's idiosyncratic risk profile, with a strategic emphasis on reinforcing corporate governance protocols and augmenting protective capital buffers. Such calibrated measures are essential to ensure the enduring resilience and stability of the credit system amidst macroeconomic turbulences and coercive sanctionary pressures.
Keywords
Subjects

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Articles in Press, Accepted Manuscript
Available Online from 02 August 2026