LAGGED CROSS CORRELATIONS ANALYSIS BETWEEN CHINA’S GDP QUARTERLY GROWTH (2016-2025) AND NPL RATIOS

This study examines the lagged cross‑correlations between China’s quarterly GDP growth and non‑performing loan (NPL) ratios of large commercial banks and rural commercial banks over the period 2016Q1–2025Q4. Using 40 quarterly observations, we find fundamentally distinct response patterns across bank types. Large commercial banks exhibit their strongest negative correlation with GDP contemporaneously (*r* = –0.61), with the magnitude steadily decaying over subsequent quarters, indicating a real‑time monitoring capacity and strong risk absorption. In contrast, rural commercial banks display a hump‑shaped lag structure, with the correlation peaking at a two‑quarter delay (*r* = –0.53), reflecting slower cash‑flow cycles of small and medium enterprises and agricultural borrowers, extended delinquency recognition windows, and protracted collateral recovery processes. The correlation magnitudes cross over between the two groups—large banks dominate at lag‑0, but rural banks become more sensitive by lag‑2, revealing a sequential “trickle‑down” risk transmission from large enterprises to downstream regional borrowers. Moreover, rural banks maintain persistently higher correlations even at lag‑3 (*r* = –0.49), underscoring weaker loss‑absorption capacity and longer‑lasting impairment effects. These findings provide quantifiable lead‑time signals for macro‑prudential supervision: a spike in large‑bank NPLs can serve as an early warning for future rural‑bank asset deterioration, with approximately a two‑quarter window for pre‑emptive counter‑cyclical policy interventions.