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Journal of Financial Services Research

Erschienen in:

19.08.2016

Retail Bank Interest Margins in Low Interest Rate Environments

verfasst von: Jaakko Sääskilahti

Erschienen in: Journal of Financial Services Research | Ausgabe 1/2018

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Abstract

This paper examines the relationship between market interest rates and retail bank interest margins. I allow for non-linearities, i.e., differences in these relationships with varying interest rate environments, which have particular implications for bank profitability and the interest rate channel of monetary policy in a low interest rate environment. I find that the interest rate spread between stocks of loans and deposits, as well as between new loans and deposits, are generally positively related to market interest rates, mainly because of highly rigid interest rates on current account deposits. In a low interest rate environment, the combination of increasing core deposit rate rigidity and variable rate loans strengthens the positive relationship between market interest rates and the interest rate spread between stocks of loans and deposits, which exerts pressure on bank profitability. The results for the interest rate spread between new loans and deposits indicate that banks react to increased deposit rate rigidity by significantly increasing spreads on new loans. Such a reaction affects the interest rate channel of monetary policy.

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The zero lower bound for deposit rates is not absolute, but the basic obstacle, at least for large negative rates, is a guaranteed zero nominal interest rate for paper currency (see e.g. Agarwal and Kimball 2015). In practice, the zero lower bound for retail deposits has been a relevant restriction, and negative rates have been rare exceptions.

This literature often uses the spread between interest revenues on assets and interest expenses on liabilities, and relative to interest-bearing assets or total assets, this spread is called the (net) interest margin. Henceforth, the interest margin denotes the difference between interest revenues and interest expenses relative to interest-bearing or total assets, and the interest rate spread is the difference between the average loan rate and the average deposit rate.

Although basic theories (e.g. Ho and Saunders 1981) are concerned with the interest rate spread between new loans and deposits, empirical studies are mainly based on the entire stocks of interest-bearing assets and liabilities.

See, e.g., Laeven and Valencia (2013)

In addition to Finland, euro area countries where variable rate loans are prevalent include Austria, Cyprus, Greece, Ireland, Italy, Luxembourg, Portugal, Slovenia and Spain (ECB 2015a).

Interest rate spreads can be defined as the sums of loan and deposit spreads. Loan spreads are differences between loan rates (new or stock) and market interest rates, and deposit spreads are differences between market interest rates and deposit rates.

Of course, the final profitability is dependent on whether banks can compensate for decreased interest rate spreads with other revenues and on whether there are other factors weakening profitability, such as significant credit losses.

The theory considers the pricing of loans and deposits and, thus, regarding the definitions in this paper, the interest rate spread between new loans and deposits.

In these empirical studies, interest margins are usually calculated based on balance sheets (Beck and Hesse (2009) being an exception). This means that these measures are based on total volumes instead of new volumes and often on all interest rate revenues and costs rather than on loan and deposit rates. Brock and Rojas Suarez (2000) compare alternative interest margins measures and find significant differences.

For Finnish banks in 2014, approximately 80 % of loans to euro area non-financial corporations and households had maturities of over 5 years.

As of March 2014.

Data on the same cooperative banks are used, e.g., in Hyytinen and Toivanen (2004).

Other papers also use data on local operating areas to measure the effects of local competition and other local characteristics on lenders’ behavior (see, e.g., Canann and Evans 2015)

A new statistical tool available from the ECB provides an easy way to compare loan and deposit prices in the euro area. It is available at: https://www.euro-area-statistics.org/?cr=eur&lg=en

The group of vulnerable euro area countries typically consist of Spain, Italy, Portugal, Greece, Cyprus and Slovenia (see e.g. ECB 2015a).

At the end of the data period, i.e., in March 2014, the outstanding amount of retail deposits was 81.1 billion euros, and the outstanding amount of money market funds was 3.2 billion euros. In addition, the share of foreign branches of public deposits was only 5.4 %.

Note that the maximum insured amount was 25,000 euros before the crisis, which increased to 50,000 euros in October 2008 and to 100,000 euros by the beginning of 2011.

Interest rates on new deposits are calculated based on a weighted average of interest rates on new term deposits and the stock of other deposits. The weights are based on the stocks of various deposits. This kind of measure is used because the number of new current account and saving deposit contracts is small. Instead, the volumes of these deposits vary over time within the contracts, and the interest rates on these deposits vary mainly based on existing terms.

The evolution of the average interest rate spread between stocks of loans and deposits of all Finnish banks is very similar to that of cooperative banks during this period, particularly in a low interest rate environment. The data for this comparison are available from the Bank of Finland: http://www.suomenpankki.fi/en/tilastot/tase_ja_korko/Pages/tilastot_rahalaitosten_lainat_talletukset_ja_korot_markkinaosuudet_ja_korkomarginaalit_k_6F9D8359.aspx

The establishment data from the business register of Statistics Finland are available for this period.

In robustness checks, I measure the competitive environments of cooperative banks using the Lerner index instead of the HHI.

The presentation of smooth transition regression analysis in this section is based on Teräsvirta et al. (2010, pp. 37–39).

For example, as interest rates on current account deposits are typically lower than those on saving deposits, they face a (zero) lower bound at different interest rates levels.

The effects of the shares of current account and saving deposits are relative to the share of term deposits, which is not included in the model because of multicollinearity.

The estimates for non-reported bank and macro controls usually indicate positive effects for market interest rate volatility, nonperforming loan shares, operating costs, and market concentration. Negative effects are observed for inflation, loan size, and fees and commissions related to total income, bank size, and the loan-deposit ratio. Not all variable estimates are statistically significant across all specifications. These results are in line with the previous empirical literature, except for the effect of inflation (e.g. Maudos and Fernández de Guevara 2004; Beck and Hesse 2009).

I estimate the STR models using the R software environment. I have modified the LSTAR model in the tsDyn package to be applicable to my empirical model with panel data. The method involves nonlinear numerical searches for the smoothness parameter γ and the location parameter c, where the starting values of the parameters are based on a grid search. After the numerical search, the regression parameters are recovered by OLS. I also use two different methods of non-linear optimization to test the robustness of the results. One is a quasi-Newton method; the other, a variant of simulated annealing belonging to the class of stochastic global optimization methods.

This result was obtained after estimating the STR model in many different ways. The estimate of the location parameter was not reasonable when the starting values based on a grid search were used, as it is far beyond the observed range of market interest rates (see Teräsvirta (1994) for further discussion). The results with different starting values and two different non-linear optimization methods revealed two optima wherein the estimated location parameters are over 10 and roughly 2. The estimates of the smoothness parameter vary quite a bit, depending on the starting values, but this had minor effects on the other estimates in the optimum, where the value of the location parameter is reasonable, i.e., roughly 2. The previous literature highlights the difficulty of estimating the smoothness parameter accurately, especially when this parameter is large (e.g. Teräsvirta 1994; Van Dijk et al. 2000).

In this specification, the estimates are reasonable with the initial starting values based on a grid search. The estimates location parameter is very close to that in the specification in column 1, indicating the robustness of the results. I also estimate this model using different starting values and methods, and the results remain robust.

In addition, within-bank variation is particularly low in the low interest rate environment.

The estimated location parameter is robust to different starting values of the non-linear parameters in all specifications when a global maximization method is used. There is some variation in the estimates of the smoothness parameter when different starting values are used, but this has little effect on the other parameters.

The location parameter value is similar to that from the first model; thus, the low interest rate environment corresponds to a level below 1 % of the 3-month Euribor.

The corresponding estimates from the main specifications are 0.39 and 0.25 for the interest rate spread between stocks of loans and deposits and the interest rate spread between new loans and deposits, respectively (see Table 2).

These are 0.59 for the market interest rate in a low interest rate environment, 0.22 for the market interest rate in a high interest rate environment, and 1.98 for the location parameter (see Table 3).

The calculation of the Lerner index is similar to that in, e.g., Lapteacru (2014).

I analyze only the spread on the stock of deposits because it is close to that of new deposits due to the definition of the average new deposit rate used in this paper (see footnote 16).

I measure NIM as interest revenues minus interest expenses divided by interest-bearing assets.

They remark that a potential non-linear effect is neglected in the existing empirical literature. In addition, as the slope of the yield curve also flattens when long-term rates are reduced directly through long-term asset purchases, this increases the pressure on net interest income and bank profitability in a low interest rate environment (Lambert and Ueda 2014). ECB ( 2015a, p. 65–68) highlights that the main effect of a low interest rate environment on bank profitability may come from a low short-term market interest rate level or a flattened yield curve, depending on the dominance of variable or fixed rate loans.

The interest rates on current account and saving deposits are calculated based on total stocks (see footnote 16).

See, e.g., De Bondt (2002); Sorensen and Werner (2006); De Graeve et al. (2007) and ECB ( 2009b). The interest rate pass-through literature examines both completeness, i.e., long-term pass-through, and the speed of adjustment, i.e., short-term pass-through. As I consider the effect of the level of the market interest rate, my analysis is related to the completeness of pass-through.

A likely for the difference is that banks must compete harder for financing of large firms, which have access to capital markets, than financing of small businesses that rely more heavily on bank financing. Of course, there may be other reasons for this increased interest rate difference, such as the relative increase in the riskiness of small businesses during the crisis.

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Titel: Retail Bank Interest Margins in Low Interest Rate Environments
verfasst von: Jaakko Sääskilahti
Publikationsdatum: 19.08.2016
Verlag: Springer US
Erschienen in: Journal of Financial Services Research / Ausgabe 1/2018
Print ISSN: 0920-8550
Elektronische ISSN: 1573-0735
DOI: https://doi.org/10.1007/s10693-016-0262-1