Innovation and Bank Capital Adequacy: An Empirical Assessment across European Economies

Massimo Arnone (), Alberto Costantiello, Carlo Drago () and Angelo Leogrande ()
Additional contact information
Massimo Arnone: Unict - Università degli studi di Catania = University of Catania
Alberto Costantiello: LUM - Università LUM Giuseppe Degennaro = University Giuseppe Degennaro
Carlo Drago: UNICUSANO - University Niccolò Cusano = Università Niccoló Cusano
Angelo Leogrande: LUM - Università LUM Giuseppe Degennaro = University Giuseppe Degennaro

Working Papers from HAL

Abstract: This paper explores the connection between innovation dynamics and the Bank Capital to Asset Ratio (CAR) in the context of 39 European nations from 2018 to 2025. With a multidimensional panel data approach that incorporates a combination of static and dynamic panel models and machine learning algorithms-specifically Decision Tree Regression-the study conducts a data-oriented analysis of the impact of various types of innovation on the resilience of the banking sector. The study differentiates innovation inputs (e.g., trademark applications, innovator share), outputs (e.g., new-tomarketing and new-to-firm product sales), and productivity factors and factors permitting a finely grained comprehension of innovation inputs and financial consequences. Cluster analysis is applied to classify countries into innovation performance groups and is followed by regression and variable importance calculations. The study identifies that process innovations executed by small and medium enterprises (SMEs) are positively linked with CAR and that information is associated with greater financial stability, whereas innovation outputs and productivity indicators at times relate inversely and register corresponding financial stress in the face of innovation-driven transitions. Further, prestage innovation inputs may raise banks' uncertainty and register systematic risk escalation. The model of a Decision Tree also reveals the sales of innovative products and labor productivity to be the most robust determinants of CAR with varied directional impacts between them. These results document the innovation-finance nexus complexity and refute the supposition that innovation equally strengthens economic prudence. The study contributes new knowledge to the literature through the combination of the assessment of financial prudency with the type of innovation and provides clear policy directions for the synchronization of innovation strategies with macroprudency aims across the European region.

Keywords: E44; O52; C38; O31; Europe. JEL CODES: G21; Decision Tree Regression; Financial Stability; Bank Capital; Innovation; Innovation Bank Capital Financial Stability Decision Tree Regression Europe. JEL CODES: G21 O31 C38 O52 E44 (search for similar items in EconPapers)
Date: 2025-08-31
Note: View the original document on HAL open archive server: https://hal.science/hal-05231617v1
References: Add references at CitEc
Citations:

Downloads: (external link)
https://hal.science/hal-05231617v1/document (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:wpaper:hal-05231617

Access Statistics for this paper

More papers in Working Papers from HAL
Bibliographic data for series maintained by CCSD ().