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In a bid to enhance the stability of banks, supervisory authorities in sub-Sahara Africa (SSA) have also adopted international bank regulatory standards based on the Basel core principles. This paper aims to investigate the effectiveness of these regulations in mitigating Bank risk (instability) in SSA. The focus of empirical analysis is on examining the implications of four regulations (capital, activity restrictions, supervisory power and market discipline) on risk-taking behaviour of banks.

This paper uses two dimensions of financial stability in relation to two different sources of bank risk: solvency risk and liquidity risk. This paper uses information from the World Bank Regulatory Survey database to construct regulation indices on activity restrictions and the three regulations pertaining to the three pillars of Basel II, i.e. capital, supervisory power and market discipline. The paper then uses a two-step system generalised method of moments estimator to estimate the impact of each regulation on solvency and liquidity risk.

The overall results show that: regulations pertaining to capital (Pillar 1) and market discipline (Pillar 3) are effective in reducing solvency risk; and regulations pertaining to supervisory power (Pillar 2) and activity restrictions increase liquidity risk (i.e. reduce bank stability).

Given some evidence from other studies which show that market power (competition) tends to condition the effect of regulations on bank stability, it would have been more informative to examine whether this is really the case in SSA, given the low levels of competition in some countries. This study is limited in this regard.

The key policy implications from the study findings are three-fold: bank supervisory agencies in SSA should prioritise the adoption of Pillars 1 and 3 of the Basel II framework as an effective policy response to enhance the stability of the banking system; a universal banking model is more stability enhancing; and there is a trade-off between stronger supervisory power and liquidity stability that needs to be properly managed every time regulatory agencies increase their supervisory mandate.

This paper provides new evidence on which Pillars of the Basel II regulatory framework are more effective in reducing bank risk in SSA. This paper also shows that the way regulations affect solvency risk is different from that of liquidity risk – an approach that allows for case specific policy interventions based on the type of bank risk under consideration. Ignoring this dual dimension of bank stability can thus lead to erroneous policy inferences.

The purpose of this paper is to use a dynamic model to investigate capital structure determinants for 178 firms listed on the Johannesburg Stock Exchange for the period 1998‐2008. The sample of firms is also used to examine the cost and speed of adjustment towards a target debt ratio.

A target adjustment model is estimated using a generalized method of moments technique to examine the cost and speed of adjustment towards a target debt ratio. The determinants of target capital structure for South African listed firms are also examined.

The results show that South African firms adjust relatively fast towards a target leverage level. It is also found that asset tangibility, growth, size and risk are positively related to leverage, while profitability and tax are negatively related to leverage. The results also suggest that capital structure decisions of South African listed firms follow both the pecking order and trade‐off theories of capital structure.

The sample chosen focused on listed firms, thus the results cannot credibly be generalized to all South African firms (listed and unlisted). Also, whilst a lot can be gleaned from the results, they may not be readily applicable to firms in other African countries.

The issue of dynamic adjustment towards a target or optimal debt ratio has not received sufficient attention in developing economies. Using data from an emerging economy, this paper attempts to fill this gap in the literature. A target adjustment model is estimated using a generalized method of moments technique.