Codes_Results_OF_Credit_Network_Roussel_2025

The zip folder contains code that replicates the tables and figures displayed in the paper "Assessment of the Output Floor in an Agent-Based Credit Network Model" (Roussel, 2025). All the code is written in R and can be run with R and/or RStudio. An additional Excel file contains empirical moments of key European financial indicators used in our study. The data generated by the code describes the effectiveness of the output floor, a key component of the Basel III finalization, within an agent-based credit network model encompassing both corporate and interbank loan markets with heterogeneous firms and banks. The model is designed to replicate the evolution of key financial indicators in the Euro Area and is calibrated to empirical output floor settings. Our data shows that the output floor is a crucial tool for enhancing banking regulation efficiency. It raises the average and reduces the dispersion of risk-weighted asset (RWA) density (i.e., the RWA-to-total assets ratio) across banks. Additionally, it improves alignment between the RWA densities of banks using the internal ratings-based and standardized approaches, thereby strengthening financial actors' confidence in banking regulation. However, accommodative monetary policy fosters risk accumulation in the banking sector, undermining the output floor's effectiveness, while tighter monetary policy has the opposite effect.该压缩包包含用于复现论文《基于智能体的信贷网络模型中的产出底线评估》（Roussel，2025）中展示的所有表格与图表的代码。所有代码均采用R语言编写，可通过R或RStudio运行。附加的Excel文件包含本研究所用核心欧洲金融指标的经验矩。本代码生成的数据用于评估产出下限（Output Floor）的实施效果——产出下限是巴塞尔协议III最终框架（Basel III finalization）的核心组成部分，相关评估基于涵盖企业信贷与银行间信贷市场、包含异质性企业与异质性银行的基于智能体的信贷网络模型（Agent-Based Credit Network Model）。本模型旨在复现欧元区核心金融指标的演化路径，并基于经验产出下限参数完成校准。本研究数据表明，产出下限是提升银行业监管效率的关键工具：其可提升全行业风险加权资产（Risk-Weighted Asset, RWA）密度（即RWA与总资产之比）的均值，同时降低其离散程度；此外，该工具还缩小了采用内部评级法与标准法的银行间的RWA密度差距，提升二者的一致性，从而增强金融市场参与者对银行业监管的信心。但宽松的货币政策会推动银行业风险积聚，削弱产出下限的监管效果；而紧缩的货币政策则会产生相反的作用。