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Valentina Flamini was an intern in the African Department when this paper was drafted. The paper benefited from comments received during an African Department seminar, and also from comments from the Offices of Executive Directors of Mr. Itam and Mr. Rutayisire.
Due to data unavailability, banks in the Comoros, Guinea Bissau, and São Tomé and Principe were not included.
Although Al-Hashimi (2007) does not test explicitly for market power, the large association he finds between high operating costs and net interest margins could be evidence of market power.
Some researchers have used loan loss provisions to measure credit risk. We opted not to follow this approach as loan loss provisions are part of the accounting breakdown of the revenue itself, which would, a priori, induce a significant negative correlation between the two variables. Loan loss provisions are also likely to account for realized losses rather risk. On the other hand, we are aware that the same loan-to-deposit ratio may imply significantly different levels of credit risk across countries if the respective practices on income verification and collaterals are different. However, the available data does not allow us to control for these effects.
Al-Haschimi (2007) finds a positive effect of credit risk on Sub-Saharan African net interest margins.
With perfect capital markets and no bankruptcy costs, the capital structure (i.e., how assets are financed) does not matter, and value can only be generated by the assets. However, with asymmetric information and bankruptcy costs, the specific way in which assets are funded could create value.
While there seems to be consensus in the literature that there are significant scale economies for small- and medium-size banks, there is disagreement with respect to large banks. A number of studies claim some economies of scale, while others find evidence of only limited cost saving and slight diseconomies in large banks. Clark (1988) and Humphrey (1990) provide useful reviews of this literature.
We opted to avoid other measures of concentration that are standard in the industrial organization literature, such as the Herfindahl-Hirschman index (HHI) or the three-firm-concentration ratio, because these measures require complete information about all banks and can be misleading. Even after correcting our sample for errors and inconsistencies, we are not able to verify the comprehensiveness of the Bankscope database given the lack of financial deepening in SSA. Moreover, a common finding in the banking literature is that these measures of concentration have only a weak relationship with profitability when market share of the firm is included in the regression equation. On the other hand, non-structural measures of concentration, such as the Rosse-Panzar, or the Lerner indices, have been shown to be poorly correlated with competition and to present major limitations when included in profitability relations. We cannot be sure that our concentration ratio effectively reflects the degree of competition in the market; however, we believe it to be less sensitive to possible omissions in the database and we are not aware of major limitations in reference to its use in profitability regressions. Hence, with the necessary caveats and without denying the possible limitations of the approach, our model specification uses the above ratio as a control for banks’ market power.
The index ranks economies on their ease of doing business. A high ranking on the index means the regulatory environment is favorable to the operation of business. This index averages the country’s percentile rankings on 10 topics, made up of a variety of indicators, giving equal weight to each topic. Due to the unavailability of data for all countries in the panel over the whole estimation period, we use the index as a qualitative feature and only consider the rankings from the Doing Business 2008 report, covering the period April 2006 to June 2007. We acknowledge that this choice might not be optimal as many countries in SSA are implementing reforms to combat corruption, so that we would expect corruption levels to go down over time. However, we preferred this solution to the alternative of drastically reducing the time span or the number of countries included in the analysis.
The output presented uses the Windmejier (2005) bias-corrected robust variance estimator.
Oil-exporting countries comprise Angola, Cameroon, Chad, Republic of Congo, Cote d’Ivoire, Equatorial Guinea, Gabon, and Nigeria.
As a robustness check, we rerun the regressions by using the Corruption Perception Index compiled by Transparency International, as a measure of the legal environment, with no improvements in statistical significance. This is also consistent with the results in Al-Haschimi (2007), which finds this variable to be insignificant in determining net interest margins in SSA banks.