Investigating Liquidity Risk Management in the Namibian Banking System

PhD (Business Administration), North-West University, Mafikeng CampusLiquidity dried up in the 2007-2009 global financial crisis as banks were not able to borrow money from each other or either obtain money from the inter-market, which led to the closure and bailing out of various financial institutions. Financial regulation and liquidity risk management are critical to financial stability and to the economy as a whole. This prompted a call to revise banking regulations and risk management, which subsequently led the Basel Committee to introduce the Basel III, which encompasses liquidity measurements. The main purpose of this thesis was to analyse commercial banks’ liquidity shocks in Namibia for the period 2009 to 2018 using the Structural VAR model (SVAR). The aim of the study was to be achieved by satisfying two sub-objectives, namely, conducting an audit of the liquidity data between 2009 and 2018, and exploring how banks were exposed to liquidity risk. Secondly, the study sought to determine the extent to which the Net Stable Funding Ratio (NSFR) which is part of Basel III can strengthen Uniform Financial Institution Rating system which is referred to by the acronym CAMELS indicators in identifying liquidity shocks. The sample consisted of four of the largest Namibian commercial banks representing 98% of total assets. These banks are namely Standard Bank, First National Bank, Nedbank and Bank Windhoek. The data sources were balance sheets that were derived from the Bank of Namibia. In addition, the Namibia Statistics Agency provided macroeconomic indicators. The empirical analysis covered the most recent global financial crisis (2007-2009) and the post crisis period, which was dominated by the shortage of liquidity in banks. Using SVAR, the study analysed the interactions of macroeconomic variables in identifying the structural shocks and provided some implications for policy and decision-making. In estimating the SVAR regression model, granger causality, impulse-response functions and forecast error variance decomposition were employed and evaluated. By auditing liquidity data between 2009 and 2018, empirical results showed that commercial banks liquidity risk in is caused by a combination of structural shocks. The granger causality, impulse-response functions and forecast error variance decomposition documented that credit risk (non-performing loans) and sensitivity to market risk (RSA_RSL) are key factors affecting commercial banks liquidity conditions in Namibia in the medium to long run. In addition, the empirical results showed that quality earnings (ROA) and capital adequacy (Tier 1 RWCR) have minimal impacts on liquidity conditions in the short run. By determining the extent to which the NSFR can strengthen CAMELS indicators in identifying liquidity shocks, the findings imply that the NSFR has minimal influence in strengthening the traditional indicators based on the CAMELS approach in identifying the liquidity shocks. The findings support the financial regulations’ focus on the traditional CAMELS approach in identifying the liquidity shocks. The study contributes to the empirical research by establishing the relationship between non-performing loans ratio (NPL) and two liquidity ratios, namely, Liquid assets to total assets (LA_TA) and Liquid asset to average total liabilities ratio (LA_ATL) as sources of liquidity shocks in banks. This is the first study to examine the relationship between NPL, LA_TA and LA_ATL from the present researcher’s knowledge and the study helped to establish the said relationships. Additionally, this study also established a relationship between rate sensitivity to assets and liabilities (RSA_RSL) and LA_TA. Again, from the present researcher’s knowledge, there is no other study that has attempted to establish the said relationships. On the other hand, the study created and used disaggregated data in the case of Net Stable Funding Ratio to demystify the relationship with other CAMELS ratios. Reforming assets quality policies, rate to sensitivity to market risk policies, earnings quality policies, capital adequacy policies, and liquidity policies such as Basel III liquidity measures can be valuable policy tools to minimise liquidity shortages and avoid insolvent banks in Namibia.Doctora