Effects of monetary policy and deposit insurance on financial policy: Does ownership structure matter? Evidence from Chinese banks
Bibliographic record
Abstract
This study empirically investigates the influence of monetary policy and deposit insurance (DI) on the financial policy of Chinese banks, taking into account the moderating role of ownership structure. The study examines an unbalanced panel of 116 banks encompassing the years 2000 to 2023. Various analytical tools, including the two-step system GMM, quadratic and nonlinear associations, three-stage least squares (3SLS) technique, and alternative measures of financial policy, have been employed to analyse the latest dataset. The findings suggest that monetary policy and deposit insurance significantly influence the financial policy adherence to the ownership structure. The ownership structure of banks has a contingent impact on financial policy. The financial policy is subject to greater influence from commercial and other banks including cooperative or rural banks compared to specialized banks. Additionally, it has been noted that reserve requirements and deposit insurance displays U-shaped relationships with financial policy. The results have imperative implications for banks and regulatory bodies that are managing key financial instruments in the complex financial landscape.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".