Performance and Merton-type default risk of listed banks in the EU: A panel VAR approach

Abstract

This paper provides empirical evidence that sheds new light into the dynamic interactions between risk and efficiency, a highly debated issue. First, we estimate three alternative measures of bank performance, by employing a directional distance function framework, along with a cost frontier and a profit function. As a second step, we calculate a Merton-type bank default risk. Then, we employ a panel VAR analysis, which allows the examination of the underlying relationships between efficiency and risk without applying any a priori restrictions. Most evidence shows that the effect of a one standard deviation shock of the distance to default on inefficiency is negative and substantial. There is some evidence of a reverse causation. As part of a sensitivity analysis, we extent our study to investigate the relationship between efficiency and default risk for banks with different types of ownership structures and across financial systems with different levels of development.

Introduction

One of the greatest challenges that financial institutions in general and banks in particular face, is coping with increasing uncertainties and accompanying risks. This has become particularly crucial in the context of the current financial turmoil, which has highlighted a miss-assessment of risk on behalf of banks, investors, as well as supervisors, with overwhelming and far reaching implications for financial stability. The importance of risk is certainly not limited to the banking sector, yet it bears greater weight for this sector, given the hefty financial and economic consequences of a bank failure (Caprio and Klingebiel, 1997).

The challenge of safeguarding financial stability has become even more vital in recent years in light of the new global financial environment that has rapidly evolved, characterized by enhanced financial liberalization and integration, rapid development of new financial products and technologies, as well as consolidation in the banking industry and increasing competition (Moshirian, 2008). All of the above pose additional pressure on banks to effectively manage their risk, while ensuring a high level of efficiency.

There are several studies that have tried to investigate the appealing relationship between efficiency and risk. Most researchers (i.e., Berger and DeYoung, 1997) have focused on the relationship between efficiency and credit risk, usually proxied by problem loans or loan loss provisions. A related strand of the literature has examined the relationship between risk and efficiency by incorporating in the efficient frontier various aspects of risk (i.e., Mester, 1996). Finally, another strand of the literature has investigated the relationship between efficiency and bank failure (Berger and Humphrey, 1992, Wheelock and Wilson, 1995) and found that failing banks tend to locate far from the efficiency frontier.

Despite the apparent interest in investigating the relationship between efficiency and risk, no empirical study has, so far, provided comprehensive evidence on the causality between them. On theoretical grounds, Goodhart et al. (2004) argue that financial stability is endogenously determined together with economic efficiency within a general equilibrium model, whilst they point to the existence of a trade-off between them. This could indicate a possible negative relationship between efficiency and risk. On the other hand, other studies (see Allen and Gale, 2004, Boyd and De Nicolo, 2005) argue that such a trade-off may not exist.

The aim of this paper is to fill this gap in the literature and to provide for the first time a comprehensive assessment of the causal relationship between bank efficiency and risk in the European banking industry by employing a novel econometric approach, the panel Vector Autoregression (VAR) analysis, which allows us to estimate the underlying dynamic relationships between inefficiency and risk without applying any a priori restrictions. In detail, we employ a three-step procedure. First, we estimate three measures of bank performance based on three alternative efficiency definitions. The first definition corresponds to productive inefficiency and is a purely technical notion, which is defined in terms of the distance to a production frontier without recourse to price information, employing the directional technology distance function developed by Chambers et al. (1996). Directional distance functions entail a flexible description of technology allowing banks to optimize by seeking simultaneously the maximum expansion of outputs and contraction of inputs that is technologically feasible (Färe et al., 2007). Cost and profit efficiency is based on the assumption that financial firms pursue either cost minimization or profit maximization, and as a result they have solid economic foundations (Berger and Mester, 1997).

In a second step, we calculate bank default risk, using stock market data. This measure has the advantage over traditional risk proxies based on accounting data, of using the forward-looking information incorporated into security prices. More specifically, it combines information about stock returns with leverage and volatility information, thus capturing the most important determinants of default risk. Finally, we employ a reduced form panel VAR analysis, which is free from imposing a priori assumptions concerning endogeneity, to examine the underlying dynamic relationships between efficiency and risk in a comprehensive way. We focus on two questions: How do the VAR’s endogenous variables, inefficiency and risk, respond dynamically to their own and other variables’ shocks? Which are the primary shocks that cause the variability in inefficiency and risk?

As part of a sensitivity analysis, we extend our work to investigate the relationship between efficiency and default risk across banks with different ownership structures (Lensink et al., 2008) and across financial systems with different levels of development (Demirguc-Kunt and Huizinga, 2000). Several studies have found that on average foreign banks perform poorly compared to private domestic institutions in developed nations (e.g., Berger et al., 2000), though results seem to be reversed in the case of developing countries (i.e., Bonin et al., 2005, Claessens et al., 2001). Thus, we examine the interaction between efficiency and risk for banks with different types of ownership by testing whether this relationship differs between foreign and domestic banks. In addition, in light of the variety of financial systems across Europe, and especially in view of the differences between ‘old’ and ‘new’ EU Member States (Uhde and Heimeshoff, 2009), we assess the role of financial development on the relationship between efficiency and risk. Demirguc-Kunt and Huizinga (2000) argue that the level of financial development has a significant impact on bank performance. To this end, we construct an index of financial development proposed by Demirguc-Kunt and Levine (1996) to examine the interaction between efficiency and risk for two groups; high and low financial development countries.

Following the above three-step procedure and the sensitivity analysis, this paper contributes to the literature in several ways. First, to our knowledge, this is the first study to examine the underlying dynamic relationship between bank efficiency and risk within a Panel VAR context, allowing us to infer empirical evidence on a highly debated issue. Second, we employ three alternative efficiency measures, as a way of strengthening the validity of our results. Third, we use a large and up-to-date dataset which covers the vast majority of listed banks in the enlarged EU. Fourth, we perform a sensitivity analysis by examining whether the relationship between risk and efficiency is influenced by the structure of bank ownership and by the level of financial development.

A quick glimpse at the results shows a negative relationship between inefficiency and the distance to default, while the causality runs from risk to inefficiency. The reverse causal relationship, from inefficiency to risk, can not be excluded for some of our alternative specifications, though the empirical evidence is weaker.

The rest of the paper is structured as follows: Section 2 presents the main hypotheses we test in our study, while Section 3 provides the empirical specification of the models employed. Section 4 deals with data issues and Section 5 discusses results. Finally, Section 6 offers some concluding remarks and possible policy implications.