.png){kind=icon}
返回
Management estimation in banking
.png){kind=icon}
PRE
AI
DOI：10.1016/j.ejor.2019.12.023.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
We present and estimate a model of management practices as an unobserved (latent) input in a standard production function of banks. We derive estimates of management at the bank-quarter level, using data for all U.S. banks from 1984 to 2016 and Bayesian techniques. We show that management practices are an important missing input in banks' operational processes. We validate our approach using repeated random sampling (Monte Carlo simulation) within a rather unfavorable environment. We also show that management is highly correlated with bank profitability (positively) and the probability of default (negatively). Our new measure compares favorably with existing measures of management derived from the residual of the regression of frontier efficiency on bank characteristics that are beyond management's capacity to change. Our model can be considered a benchmark to estimate good management practices, to analyze their sources, and to establish good management as an important determinant of efficient and sound banking. (C) 2019 Elsevier B.V. All rights reserved.
Keyword:
OR in banking
Management practices
Cost function
Bayesian methods
Monte Carlo simulation
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6
论文数:
2.2W
被引数:
6.4W
机构
引用论文
.png){kind=icon}
分享收藏
查看更多内容