Determinants of bank interest margins: Impact of maturity transformation

Abstract

This paper explores the extent to which interest risk exposure is priced in bank margins.Our contribution to the literature is twofold: First, we present an extended model of Ho and Saunders (1981) that explicitly captures interest rate risk and returns from maturity transformation. Banks price interest risk according to their individual exposure separately in loan and deposit rates, but reduce these charges when they expect returns from maturity transformation. Second, using a comprehensive dataset covering the German universal banks between 2000 and 2009, we test the model-implied hypotheses not only for the commonly investigated net interest income, but additionally for interest income and expenses separately.Controlling for earnings from bank-individual maturity transformation strategies, we find all banks to charge additional fees for macroeconomic interest volatility exposure. Microeco- Non-technical summaryBanks are intermediaries between investors and entrepreneurs. They transform long-term, illiquid and risky loans into safe deposits that are due within short notice. By doing so, they take risks, for which they are remunerated. Besides, they can generate income by making use of their market power and by setting their credit and deposit conditions accordingly. In a theoretical model, we show that the bank rates are set in accordance with the costs and earnings caused by the loans and deposits. In addition, banks levy premia for credit and interest rate risk, and for the access to the capital market. We derive the following empirically testable hypotheses:The margins on the asset side should be the higher, the stronger the market power, the more volatile the interest rates and the credit risk and the greater the exposure to interest rate risk.The model also predicts that banks smooth their interest rates (relative to the interest rates observed on the capital market). Accordingly, on the liability side, we expect the same factors to have an impact, expect for the credit risk, which is here not relevant. In an empirical study of all German universal banks for the period 2000 -2009, we obtain the following results:1. The statements derived from the theoretical model can be confirmed in our study, in particular we find that the higher the market power the higher the interest income margin and the lower the interest expense margin.2. The interest rate margins increase for all banks, in the event that the interest rates become more volatile. Additionally, for banks from the savings and credit cooperative sectors, we see the smoothing of bank rates that is predicted by the theoretical model. Nichttechnische Zusammenfassung

Determinants of Banks’ Net Interest Margin: Evidence from the Euro Area during the Crisis and Post-Crisis Period

“…The statistically significant coefficient of operating costs shows that banks that operate with higher costs need to increase net interest margins to cover expenses, confirming the findings of previous studies [18,22,58]. Furthermore, we found that better managed banks are characterized by higher net interest margins, as shown by the positive and statistically significant impact of the efficiency variable.…”

Monetary and Financial Instability and European Bank Interest Margins

“…Hanweck & Ryu (2005) developed a dynamic model of bank behaviour that explains NIM changes for different groups of banks in response to credit, interest-rate, and term-structure shocks. More recently, Carbó-Valverde & Fernández (2007) applied the Ho & Saunders (1981) model to a multi-output framework, Lin et al (2012) study the determinants of NIM and their impact on bank diversification, Entrop et al (2015) analyse the extent to which interest risk exposure is priced into bank margins, and Islam & Nishiyama (2016) study the determinants of NIM in four South Asian countries. This paper follows in the footsteps of this research, estimating several specifications of equation (1):…”

Forecasting the Net Interest Margin and Loan Loss Provision Ratio of Banks in Various Economic Scenarios: Evidence from Poland

“…Empirical research stemming from these contributions has focused on the use of additional control variables. Most studies use proxies for credit risk (Maudos and de Guevara, 2004), interest rate risk (Entrop et al, 2015;Hawtrey and Liang, 2008;Maudos and de Guevara, 2004), and operating costs (Liebeg and Schwaiger, 2006;Entrop et al, 2015) as the key explanatory variables underpinning NIM; market structure and institutional factors are also controlled for in much of the available research.…”

“…Many papers take into account market interest rates of different maturities and/or their respective standard deviation to consider the development of both the short and the long end of the yield curve. Only a few papers include such additional macroeconomic variables as inflation (Horvath, 2009;Entrop et al, 2015) and market interest rate spreads (Rumler and Waschiczek, 2016).…”