Challenges in the Era of Globalization - iaabd

Challenges in the Era of Globalization
Edited by Emmanuel Obuah
since 2003, SSA bank market power and spread have been falling. In general, the conventional Lerner
figures indicate 26% price mark-up over marginal cost during the period, 2000-2007, whereas the
estimated funding and efficiency-adjusted Lerner indices are around 57% and 59% respectively. As in the
case of Koetter et al (2008) for US banks, the figures of efficiency-adjusted Lerner exceeds that of
conventional index. Likewise the magnitude of funding-adjusted Lerner is on average more than the
conventional Lerner. These figures indeed suggest that the former figures underestimate the degree of
market power and thus justify the use of the three estimations in this analysis. The African banks have
increased their use of non-deposit funding over the period. In 2000, the average non-deposit funding, our
proxy for funding strategy was 7.8% then increase to 14.42% in 2004. The magnitude of non-deposit
funding then fell by 59% to 5.84% in 2007. Similar trends are reported for internal cash flow financing.
Risk aversion and credit risk increased in the period being analyzed; only falling in 2007. However, the
increase in risk aversion (equity ratio) must be analyzed in the context of the capitalization level in Africa.
Labor cost increased over the period while implicit payment increases in mid 2000s (i.e. 2001-2004). The
size of the bank proxied by the dollar amount of total assets was relatively stable during the period under
study. So was the cost to income ratio.
Table 1: Summary statistics averaged for the period 2000-2007
2000 2001 2002 2003 2004 2005 2006 2007
Bank spread 0.039 0.059 0.064 0.078 0.077 0.072 0.061 0.045
Conventional Lerner 0.104 0.115 0.178 0.255 0.257 0.245 0.263 0.248
Funding-adjusted Lerner 0.270 0.423 0.466 0.537 0.529 0.500 0.469 0.422
Efficiency-adjusted Lerner 0.292 0.454 0.493 0.556 0.545 0.501 0.485 0.432
Concentration 0.657 0.636 0.632 0.603 0.569 0.553 0.557 0.581
Internal fund 0.050 0.072 0.066 0.085 0.088 0.063 0.071 0.060
Non-deposit fund 0.078 0.103 0.131 0.144 0.144 0.109 0.096 0.058
Credit risk 0.275 0.392 0.395 0.446 0.466 0.432 0.411 0.354
Risk aversion 0.078 0.120 0.118 0.126 0.134 0.133 0.114 0.100
Bank size ($’million) 333.8 459.7 553.6 737.7 865.1 496.3 524.2 647.1
Implicit payment 0.010 0.018 0.018 0.020 0.022 0.019 0.017 0.011
Labor cost 0.012 0.019 0.022 0.024 0.024 0.023 0.020 0.017
Efficiency ratio 0.278 0.484 0.487 0.472 0.507 0.497 0.408 0.336
Non-interest income 0.097 0.127 0.162 0.166 0.163 0.150 0.142 0.132
Monetary policy 0.220 0.216 0.197 0.302 0.182 0.378 0.320 0.538
Source: WDI, Bankscope and author’s own calculations
All the calculations are in percentages except bank size which in million of US Dollars
Evaluation of bank spread in SSA
The objective of this paper is to investigate empirically the relationship between spread and monetary
policy. To this effect, the paper follows Maudos and Fernandez de Guevara (2004), to estimate equation
(1) using fixed effect. The method captures specific characteristics of individual banks by employing the
within-group estimators. The Hausman test allows the null hypothesis of absence of correlation between
individual effects and the explanatory variables to be rejected in all cases, thus the GLS estimator of the
random effect model being inconsistent. The regression results relating bank spreads to credit risk, labour
cost, cash flows, funding strategy, bank market power and implicit payments are presented in table 2. It
includes macro variables to investigate whether banks profit from tightening of monetary policy
indicators. The different columns reported relate to different empirical approaches to Lerner index used:
column 1 for conventional Lerner index, column 2 for funding-adjusted Lerner index and column 3 for
efficiency-adjusted Lerner index. The results, in general, show that all the variables considered in the
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