This chapter examines the acceptable R-square in social science empirical modelling with particular focus on why a low R-square model is acceptable in empirical social science research. The paper shows that a low R-square model is not necessarily bad. This is because the goal of most social science research modelling is not to predict human behaviour. Rather, the goal is often to assess whether specific predictors or explanatory variables have a significant effect on the dependent variable. Therefore, a low R-square of at least 0.1 (or 10 percent) is acceptable on the condition that some or most of the predictors or explanatory variables are statistically significant. If this condition is not met, the low R-square model cannot be accepted. A high R-square model is also acceptable provided that there is no spurious causation in the model and there is no multi-collinearity among the explanatory variables.

This paper provides a comprehensive review of the recent evidence on financial inclusion from all the regions of the World. It identifies the emerging themes in the financial inclusion literature as well as some controversy in policy circles regarding financial inclusion. In particular, I draw attention to some issues such as optimal financial inclusion, extreme financial inclusion, how financial inclusion can transmit systemic risks to the formal financial sector, and whether financial inclusion and exclusion are pro-cyclical with changes in the economic cycle. The key findings in this review indicate that financial inclusion affects, and is influenced by, the level of financial innovation, poverty-levels, the stability of the financial sector, the state of the economy, financial literacy, and regulatory frameworks which differ across countries. Finally, the issues discussed in this paper opens up several avenues for future research

Purpose: This paper aims to investigate the influence of financial development on non-performing loans (NPL). Design/methodology/approach: The model used in this study follows the NPL model of Louzis et al. (2012), Ozili (2015) and Beck et al. (2015). Findings: The findings indicate that financial development, measured as foreign bank presence and financial intermediation, are positively associated with NPLs. Also, bank efficiency, loan loss coverage ratio, competition and banking system stability are inversely associated with NPLs, while NPLs are positively associated with banking crises and bank concentration. In the regional analysis, NPLs are negatively associated with regulatory capital and bank liquidity, implying that banking sectors with greater regulatory capital and liquidity experience fewer NPLs. Practical implications: National bank regulators/supervisor should not only consider the role that financial development structures play in influencing aggregate NPLs but also ensure that thorough supervision of the lending practices of banks is in place as well as the active monitoring of the financial intermediation process in the country. Originality/value: The study is the first to use a global sample to examine the direct relationship between NPL and financial development.

Purpose: The purpose of this paper is to investigate the determinants of banking stability in Africa. Design/methodology/approach: The authors present four measures of banking stability embedding banks’ loan loss coverage ratio, insolvency risk, asset quality ratio, and level of financial development, thereby allowing analysis of banking stability determinants from four complementary perspectives: protection for downside credit losses, distress arising from insolvency risk, non-performing loans, and financial development. The authors use the regression methodology to estimate the impact of financial structure, institutional, bank-level factors on bank stability. Findings: The findings indicate that banking efficiency, foreign bank presence, banking concentration, size of banking sector, government effectiveness, political stability, regulatory quality, investor protection, corruption control and unemployment levels are significant determinant of banking stability in Africa and the significance of each determinant depends on the banking stability proxy employed and depends on the period of analysis: pre-crisis, during-crisis or post-crisis. Practical implications: Banking supervisors in African countries should consider the role of financial structure and institutional quality for banking stability in the African region. Originality/value: This study is the first to examine banking stability determinants in Africa that takes into account institutional quality and financial structure.

We review the recent academic and policy literature on bank loan loss provisioning (LLP) to identify several advances in the literature, to\ud highlight some challenges in LLP research and suggest possible directions for future research with some concluding remarks. Among other things, we observe some major advancement in country-specific and cross-country analyses and substantial interaction between LLPs and existing prudential, accounting, institutional firm characteristic, cultural, religious, tax and fiscal framework. We observe that managerial\ud discretion in provisioning does not necessarily generate LLP estimates that reflect the true and underlying economic reality of banks' credit risk\ud exposure but rather managerial discretion in provisioning is strongly linked to income smoothing, capital management, signalling and other\ud objectives. We also address several issues including the ethical dimensions of income smoothing, motivations and constrains to income\ud smoothing, methodological issues in the bank loan loss provisions literature and the dynamic loan loss provisioning experiment. Moreover, we suggest several avenues for further research such as: finding a balance between sufficient LLPs which regulators want versus transparent LLPs which standard setters want; the sensitivity of abnormal (specific and general) LLPs to changes in equity; the persistence of abnormal LLPs following CEO exit; country-specific interventions that induce LLP procyclicality in emerging countries; investigating LLP behaviour in the post-financial crisis sample period; the impact of Basel III on banks' provisioning discretion; LLP behaviour among systemic and non-systemic financial institutions; etc. We conclude that, because provisioning models are only as good as the assumptions underlying such models as well as the accuracy of the inputs included in such models, regulators need to pay attention to how much discretion banks and lending institutions should have in determining reported provision estimates, and this has been a long standing issue