Akademik Veri Yönetim Sistemi
Borsa Istanbul Review, 2026 (SSCI, Scopus)
This paper provides causal estimates of how balance-sheet exposure to floating-rate debt transmits monetary tightening into corporate default risk. Leveraging the June 2023 policy shift in Türkiye and a large administrative dataset, we employ a two-part Double Machine Learning framework to disentangle selection from causation, distinguishing between the extensive margin of exposure and the intensive-margin effects. We find that while the average effect is modest, indicating aggregate resilience, treatment effects are markedly heterogeneous and economically significant for a vulnerable subset. Sensitivity is concentrated in firms with weak internal risk ratings, low liquidity, and high exposure shares, whereas exporters and manufacturers are relatively insulated. This relative resilience is consistent with standard transmission mechanisms: exporters and manufacturing firms are more likely to generate foreign-currency revenues and benefit from exchange-rate pass-through, while their working capital cycles and pricing structures allow for partial absorption of higher interest expenses, attenuating the balance-sheet impact of monetary tightening. Moving beyond estimation, we introduce 'explainable heterogeneity' by applying SHAP analysis to causal forest estimates, thereby transparently mapping firm traits to causal sensitivity.