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The purpose of this paper is to investigate the impact of ownership structure on bank performance in EU-15 countries. Specifically, it examines to what extent shareholder type and the degree of shareholder concentration affect the banks’ profitability, risk and technical efficiency.

This study uses a sample of 1,459 banks operating in EU-15 countries from 2011 to 2015. It constructs a set of continuous variables capturing the ownership nature, the concentration and their interactions, and estimates an instrumental variable random effect (IV-RE) model. In addition, a panel data stochastic frontier analysis is conducted to estimate the time-varying technical efficiency for profitability and costs.

The empirical analysis shows that bank performance is affected by shareholder type. When regressed against the entrenchment behavior of the controlling owner hypothesis, banks with large-block shareholders are more profitable, less risky and more profit efficient. Further, ownership concentration reverts the negative effect related to the institutional, bank and industry ownership.

The results support the hypothesis that concentrated ownership helps to overcome agency problems. They also confirm that managerial involvement in banks’ capital enhances a bank’s profit and its volatility.

To the best of the authors’ knowledge, this is the first study to consider the ownership nature, the concentration and their interaction using continuous variables, which allows for more precise inferences. The results provide new evidence that bank profitability, cost efficiency and risk are affected by the type of direct shareholders.

This study aims to propose a non-linear model to describe the effect of macroeconomic shocks on delinquency rates of three kinds of bank loans. Indeed, a wealth of literature has recognized significant evidence of the linkage between macro conditions and credit vulnerability, perceiving the importance of the high amount of bad loans for economic stagnation and financial vulnerability.

Generally, this linkage was represented by linear relationships, but the strong dependence of bank loan default on the economic cycle, subject to changes in regime, could suggest non-linear models as more appropriate. Indeed, macroeconomic variables affect the performance of bank’s portfolio loan, but such a relationship is subject to changes disturbing the stability of parameters along the time. This study is an attempt to model three different kinds of bank loan defaults and to forecast them in the case of the USA, detecting non-linear and asymmetric behaviors by the adoption of a Markov-switching (MS) approach.

Comparing it with the classical linear model, the authors identify evidence for the presence of regimes and asymmetries, changing in correspondence of the recession periods during the span of 1987–2017.

The data are at a quarterly frequency, and more observations and more extended research periods could ameliorate the MS technique.

The good forecasting performance of this model could be applied by authorities to fine-tune their policies and deal with different types of loans and to diversify strategies during the different economic trends. In addition, bank management can refer to the performance of macroeconomic conditions to predict the performance of their bad loans.

The authors show a clear outperformance of the MS model concerning the linear one.