Data_Capital Buffer

This dataset accompanies the research work about “Capital Buffer and Macroeconomic Factors Affecting Credit Risk in Commercial Banks". The study uses balanced panel data from five systemically important Nepalese commercial banks covering eleven fiscal years (FY 2013/14–2023/24), resulting in 55 observations. The dataset includes dependent variables: Loan Loss Provisions (LLP, NPR billion) and Non-Performing Loan Ratio (NPL, %), representing credit risk. Independent variables include Paid-Up Capital (PUC, NPR billion), Discretionary Capital Buffer (DCB, % above regulatory minimum CAR), GDP Growth Rate (GDP, %), Inflation Rate (INF, %), and Unemployment Rate (UER, %). The study applies panel regression techniques including pooled OLS, fixed effects, and random effects models to examine the relationship between bank capital structure, macroeconomic conditions, and credit risk in Nepalese commercial banks.

本数据集配套于题为《商业银行资本缓冲与影响信用风险的宏观经济因素》的研究工作。本研究采用尼泊尔5家系统重要性商业银行（systemically important commercial banks）2013/14财年至2023/24财年共11个财年的平衡面板数据，最终得到55组观测值。数据集涵盖两类因变量：贷款损失准备金（Loan Loss Provisions, LLP，单位：十亿尼泊尔卢比）与不良贷款率（Non-Performing Loan Ratio, NPL，单位：%），二者均作为信用风险的代理变量。自变量则包括实缴资本（Paid-Up Capital, PUC，单位：十亿尼泊尔卢比）、相机抉择资本缓冲（Discretionary Capital Buffer, DCB，即高于监管最低资本充足率（Capital Adequacy Ratio, CAR）的百分比）、GDP增长率（GDP Growth Rate, GDP，单位：%）、通货膨胀率（Inflation Rate, INF，单位：%）以及失业率（Unemployment Rate, UER，单位：%）。本研究运用混合普通最小二乘法（pooled OLS）、固定效应模型与随机效应模型等面板回归方法，探究尼泊尔商业银行资本结构、宏观经济环境与信用风险之间的关联关系。