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4405. A Bayesian Hierarchical Approach to Analyze the Heterogeneous Influence of Banking Risk on Cost Efficiency
Invited abstract in session TB-63: Risk Management and Cryptoassets, stream OR in Banking, Finance and Insurance: New Tools for Risk Management.
Tuesday, 10:30-12:00Room: S14 (building: 101)
Authors (first author is the speaker)
| 1. | Pilar Gargallo
|
| Facultad de EconomÃa y Empresa, Universidad de Zaragoza | |
| 2. | Manuel Salvador
|
| Facultad de Económicas, Universidad de Zaragoza |
Abstract
In the past two decades, European banking sectors experienced a significant integration and expansion on global financial markets. This period, characterized by intense competition and the aftermath of the global financial crisis (2007-2009), sparked growing concern regarding the risk taken on by banking systems and its impact on financial performance. Although there is an abundant literature on this topic, uncertainty remains about the extent and nature of the effects of banking risk. Moreover, previous studies that examined this relationship often assume a uniform effect of risk on banking efficiency, without considering the possibility that the risk taken on by banks may have diverse effects depending on the characteristics of the bank and the conditions of the operating environment. To address this issue, we propose a Bayesian stochastic frontier model for unbalanced data. It includes commercial banks operating in European Union countries in 2004-2020 to estimate the evolution of their cost efficiency. We assume the efficiency depends on the size of the bank and the levels of risk it assumes. In a hierarchical model, we postulate that the influence exerted by these characteristics depends on the environment in which the bank operates, including the country and the industry. We obtained the economic and financial data from Orbis Bank Focus (2004-2016) and Orbis (2017-2020), while industry and country data from the World Bank's World Development Indicators database.
Keywords
- Finance and Banking
- Financial Modelling
- Risk Analysis and Management
Status: accepted
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