# **3. Methodology**

In this section we discuss and present the methodological framework used to estimate the main drivers of bank spreads across various countries throughout the world. We adopt the method devised by Saunders and Schumacher (2000) who built on Ho and Saunders (1981) to construct a multi-country framework for decomposing bank margins into (i) an institutional and regulatory component, (ii) a market structure component conveying the degree of banking market competition, and (iii) a macroeconomic risk premium component.

Saunders and Schumacher (2000) do not directly disaggregate the share of the spreads, into three groups of factors, however it is possible and that is what we do in this paper. Initially, we derive the share of the spreads that are attributed to institutional and regulatory factors; secondly, the share of the spreads that are attributed to banking market competition; and thirdly, the share of the spreads that are attributed to macroeconomic factors. These three shares will be derived and compared across all the countries in our sample. Then we rank in terms of the different types of drivers of the spreads and we proceed to analyze the main drivers of the spreads in Brazil thoroughly.

The estimation procedure consists of three steps; the first two following Saunders and Schumacher (2000) and a third step to derive the share each factor contributes to the bank spread as follows:

1. In Step 1, we regress a cross section of NIMs on banks specific variables such as (i) the ratio of non-interest bearing assets to total assets, (ii) the ratio of non-performing loans to total loans, and (iii) the capital asset ratio. In the regression, the three explanatory variables convey the importance of institutional and regulatory factors and leave the constant term of the regression to convey the unexplained part of the spreads. In that sense the constant term is, in the literature, called a “pure” spread, which then contains information about macroeconomic factors and the degree of banking competition, as interpreted by Saunders and Schumacher (2000). From this exercise, the pure spreads should theoretically be equal across all banks in any country at any point in time. However, pure spreads can be shown to vary across countries (and over time) according to the degrees of bank competition and interest-rate volatility in each country.

2. In Step 2 of the estimation procedure, the constant term from the regression in Step 1 (the pure spread) is regressed against macro variables, such as the volatility of interest rates and economic growth rates. In Step 2, the constant term captures the effect of market structure on the determination of the pure spread. This market structure is, in the literature, generally interpreted as the degree of market competition; i.e. the higher the constant term is in Step 2 regressions, the lower the degree of banking competition.

3. We add a third step to the estimation procedure. While Saunders and Schumacher (2000) provide the methodology, we exploit the framework to derive, in a systematic way across countries, the level and the percentage share of the spreads that are explained by (i) institutional and regulatory factors, (ii) banking competition, and (iii) macroeconomic factors, respectively.

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