‘adjusted’ SELIC rate. Their study finds that macroeconomic variables are significant and explain a substantial part of the adjusted SELIC rate (R<sup>2</sup> =0.86). Then they investigate various microeconomic factors in an effort to explain the remainder of the spread not previously explained by macroeconomics factors. Their analysis finds that the macroeconomic factors are the most significant drivers of interest spreads in Brazil. We use a different methodology, a larger dataset and a longer time period to evaluate the results of de la Torre eta al. (2006) and gauge the effects of the significant growth in Brazil in the middle of the 2000s and the subsequent global crisis.

Research by Afanasieff, Lhacer and Nakane (2002) use the technique developed by Ho and Saunders (1981), to estimate the variables affecting spreads in Brazil measured as the difference between loan and deposit rates in Brazilian banks. The study uses several variables such as the number of bank branches, operating costs, bank leverage and the ratio of non interest-bearing deposits to total operational assets to calculate the pure spread or the macro part of the total spread. They use an unbalanced panel excluding misreported and outliers data, which possibly diminishes the power of their results. Furthermore, the definition of the spread, defined as the difference between the loan rate measured by the average rate charged on fixed-rate free-allocated operations and the deposit rate measured by the rate paid on 30-day certificates of deposits, is not wholly representative of the spreads faced by banks.

The loan interest rate is the average rate charged on fixed rate free-allocated operations, which excludes floating rates. Therefore, the spread calculated is not representative of the spreads in Brazil, in terms of maturity and fixed or floating rates. We evaluate their finding that spreads in Brazil are mainly caused by macroeconomic factors by using a dataset that extends to 2010, and includes the global crisis.

Our approach uses the same methodology used by Afanasieff, Lhacer and Nakane (2002)first introduced by Ho and Saunders (1981) and expanded by Saunders and Schumacher (2000). We use the Net Interest Margin (NIM) as a proxy to interest spreads in Brazil. Three institutional and regulatory (micro) variables are used to explain the variation in the NIM leaving the rest to be explained by macroeconomic and competition factors. These variables are consistently collected by BankScope and are comparable between banks, countries and regions. Hence, the methodology adds significant value making the analysis of spreads more consistent and comparable across banks and countries.

- The first variable is payments by banks of implicit interest on deposits through service charge remissions and other forms of savers subsidy because of regulatory restrictions on explicit interest payments. Implicit interest payments are measured by non-interest expense minus other operating income divided by total average assets.

- The second variable is the bank’s opportunity cost of depositing reserves with the monetary authorities. The economic cost of holding reserves is calculated by the ratio of non-interest earning assets to total assets variable.

- The third variable is capital reserves that banks decide to hold to protect themselves against anticipated and unanticipated credit risk. Consequently, banks that have high capital ratios for regulatory or credit reasons are likely to pass on the cost to borrowers. We proxy the extra capital held by banks using the equity over total assets variable.

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