Browsing by Author "Chisunga, David"

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    Causal Relationship between financial sector development and economic growth: a case of Zimbabwe
    (IOSR Journal of Business and Management, 2015-04-20) Chisunga, David
    This paper aims to investigate the impact of financial sector development on economic growth in Zimbabwe, the reason being that no such research has been carried out in Zimbabwe. The research utilized secondary data for the period 1995 to 2008.Granger causality test is used to test the causality between economic growth and four financial sector development indicators. Johansen co-integration approach is used to test the long run relationship between economic growth and financial sector development indicators. The paper found out that granger causality runs from economic growth to financial sector development. The results support some empirical evidence that postulates that the granger relationship runs from economic growth to financial development and is there is a positive relationship in the long run. The study provides empirical evidence that economic growth granger causes financial sector development and there are positively related in the long run. Therefore, it is important that the government of Zimbabwe should implement policies that fosters economic growth and this will subsequently promotes financial sector development
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    Modelling the Sensitivity of Zimbabwean Commercial Banks’ Non-performing Loans to Shocks in Macro-economic Variables and Micro-economic Variables: (2009-2014)
    (World Journal of Operational Research, 2017-06-21) Muvingi, Jacob; Sauka, Kudzai; Chisunga, David; Chirume, Crispen
    This paper used complementary panel data models that are fixed effect regression model and panel vector auto regression model. The study was motivated by the hypothesis that both macroeconomic and microeconomic variables have an effect on the loan quality. The first part of the research was to determine the specific macro and microeconomic variables that give rise to the non-performing loans (NPLs) using fixed effect regression model. The empirical findings of this study provide evidence that nonperforming loans depends on macro and micro economic variables, the trend analysis of Zimbabwean commercial banks’ shows an upward movement of over the period of study. The study found out that Gross domestic product (GDP), Inflation, loan deposit ratio and bank size had a statistical significant effect on the level of non-performing loans (NPLs). The second part was mainly to model the dynamic relationship of all the variables that were found to affect nonperforming loans (NPLs); this was done through impulse response analysis based on PANEL VAR model. One standard shock to credit growth will be greatly felt in the sixth year, whereas of size of the bank will have a great negative impulse in the seventh year