1,720,961 research outputs found
Assessing the financial inclusion of micro-, small, and medium enterprises(MSMEs) in South Africa: 2010 and 2020 FinScope MSME data
No full textMagister Commercii - MComThe financial inclusion of micro-, small, and medium enterprises (MSMEs) as major stakeholders in the economy remains meagre. MSMEs are the strongest economic activity drivers worldwide, yet many researchers have studied the effect of financial inclusion on MSMEs as it has become a global priority. International and local studies have agreed that removing certain financial system constraints can improve the financial inclusion status of MSMEs. Yet, local studies focused on this concept for South African MSMEs are scarce. The objective of this study is to assess the financial inclusion of micro-, small, and medium enterprises (MSMEs) in South Africa. This study offers the first of its kind to use FinScope MSME 2010 and 2020 surveys to assess the financial inclusion of MSMEs in South Africa and uses the Multiple Correspondence Analysis (MCA) to derive a financial inclusion index to assess the financial inclusion status of MSMEs. This study aims to fill the gap in the literature by using recent data and a different methodology to measure the financial inclusion of MSMEs in South Africa. The relationship between the computed MSME financial inclusion index and various explanatory variables is tested using the Ordinary Least Squares regression model. Thereafter, the likelihood of being financially excluded is measured by running probit regressions
Investigating the relationship between financial inclusion and poverty in South Africa
No full textMasters of CommerceThe literature on financial inclusion and poverty connections has received considerable attention recently. There exist a scarcity of local studies examining the relationship between financial inclusion (FI) and poverty. Precisely, there is a lack of local studies who previously used FinScope data to investigate the mentioned relationship in South Africa. This study is motivated to fill the gap. To achieve the aims, the study will source data from FinScope (a secondary data) for the periods of 2011 and 2016. The Foster-Greer-Thorbecke indices were used to measure the level of poverty, while the lower-bound poverty (LBPL) line was used to differentiate the poor from the non-poor. Principal Component Analysis (PCA) was also applied to derive the financial inclusion index (FII). Probit regressions were run to measure the likelihood of being poor and being financially excluded. Ordinary Least Squares were run to identify the nature of the relationship between the dependent and the independent variables. Lastly, bivariate regression was also run to test the relationship between poverty and financial exclusion. The empirical findings indicated that the South African financial system is inclusive. Unemployment and financial language restricted financial service access. The frequently used financial services were borrowing and funeral cover. Black African female with low education residing in rural areas and unemployed were poorer. The rich elderly white man from the urban areas of the Western Cape and Gauteng who are highly educated, were more likely to be financially included. The regression analysis showed that the female was more likely to be financially included yet poor. It is also found that Gauteng residents were less likely to be poor. Also, individuals from a bigger household were less likely to be excluded. The other results showed that individuals with higher real per capita income enjoyed much lower probability of being financially excluded, and they are mainly white individuals living in urban areas
Investigating financial inclusion in rural households: A South African case
No full textMagister Commercii - MComPeople residing in rural areas generally struggle with many socio-economic problems, such as transport, health access, employment opportunities, poverty, inequality, access to essential services and facilities (e.g., piped water, electricity) as well as access to financial services. The global community has over the years came up with progressive measures directed at economic development and improvement of living standards, with one of them being financial inclusion (FI). FI is seen as one of the strategies to eradicate poverty, reduce unemployment and inequality as well as enhancing an inclusive economic growth.
This study investigated financial inclusion in rural households of South Africa, using the Finscope data (2011 and 2016), with the aim of examining the extent of financial inclusion in rural households
Investigating financial inclusion in rural households: A South African case
Get PDFMagister Commercii - MComPeople residing in rural areas generally struggle with many socio-economic problems, such as transport, health access, employment opportunities, poverty, inequality, access to essential services and facilities (e.g., piped water, electricity) as well as access to financial services. The global community has over the years came up with progressive measures directed at economic development and improvement of living standards, with one of them being financial inclusion (FI). FI is seen as one of the strategies to eradicate poverty, reduce unemployment and inequality as well as enhancing an inclusive economic growth.
This study investigated financial inclusion in rural households of South Africa, using the Finscope data (2011 and 2016), with the aim of examining the extent of financial inclusion in rural households
Investigating the relationship between financial inclusion and poverty in South Africa
Get PDFMasters of CommerceThe literature on financial inclusion and poverty connections has received considerable attention recently. There exist a scarcity of local studies examining the relationship between financial inclusion (FI) and poverty. Precisely, there is a lack of local studies who previously used FinScope data to investigate the mentioned relationship in South Africa. This study is motivated to fill the gap. To achieve the aims, the study will source data from FinScope (a secondary data) for the periods of 2011 and 2016. The Foster-Greer-Thorbecke indices were used to measure the level of poverty, while the lower-bound poverty (LBPL) line was used to differentiate the poor from the non-poor. Principal Component Analysis (PCA) was also applied to derive the financial inclusion index (FII). Probit regressions were run to measure the likelihood of being poor and being financially excluded. Ordinary Least Squares were run to identify the nature of the relationship between the dependent and the independent variables. Lastly, bivariate regression was also run to test the relationship between poverty and financial exclusion. The empirical findings indicated that the South African financial system is inclusive. Unemployment and financial language restricted financial service access. The frequently used financial services were borrowing and funeral cover. Black African female with low education residing in rural areas and unemployed were poorer. The rich elderly white man from the urban areas of the Western Cape and Gauteng who are highly educated, were more likely to be financially included. The regression analysis showed that the female was more likely to be financially included yet poor. It is also found that Gauteng residents were less likely to be poor. Also, individuals from a bigger household were less likely to be excluded. The other results showed that individuals with higher real per capita income enjoyed much lower probability of being financially excluded, and they are mainly white individuals living in urban areas
Investigating the relationship between financial inclusion and poverty in South Africa
No full textMagister Commercii - MComThe literature on financial inclusion and poverty connections has received considerable attention recently. There exist a scarcity of local studies examining the relationship between financial inclusion (FI) and poverty. Precisely, there is a lack of local studies who previously used FinScope data to investigate the mentioned relationship in South Africa. This study is motivated to fill the gap. To achieve the aims, the study will source data from FinScope (a secondary data) for the periods of 2011 and 2016. The Foster-Greer-Thorbecke indices were used to measure the level of poverty, while the lower-bound poverty (LBPL) line was used to differentiate the poor from the non-poor. Principal Component Analysis (PCA) was also applied to derive the financial inclusion index (FII). Probit regressions were run to measure the likelihood of being poor and being financially excluded. Ordinary Least Squares were run to identify the nature of the relationship between the dependent and the independent variables. Lastly, bivariate regression was also run to test the relationship between poverty and financial exclusion
Socio-economic correlates with the prevalence and onset of diabetes in South Africa: Evidence from the first four waves of the National Income Dynamics Study
No full textWe make use of multiple waves of National Income Dynamics Study data, from 2008 to 2015, to
investigate the socio‐economic factors that correlate with the prevalence and onset of diabetes. Our
analysis follows a cohort of 3470 older adults aged forty and above, who are interviewed four times
over a six-year period. We use linear probability models and estimate the likelihood of diabetes as a
function of age, race, gender, education, income, exercise, and obesity. Our primary findings are that
age and obesity correlate strongly with diabetes, while income does not have a statistically significant
effect, conditional on the other covariates. Our regression estimates indicate that, of individuals who
reported not being diabetic in Wave 1, those who were obese and morbidly obese were 12.9 and 16.7
percentage points more likely to have experienced the onset of diabetes respectively, relative to those
with a BMI in the healthy range. In addition, frequent exercise does appear to have a slight protective
effect against the onset of diabetes, and there is some evidence that better educated people have a
lower risk of onset of the disease.Velenkosini Matsebula: Researcher, SALDRU, UCT. Email: [email protected], corresponding author.
Vimal Ranchhod: Chief Research Officer, SALDRU, UCT. Email:[email protected]
Acknowledgements:
Funding for this research from the Department of Planning, Monitoring and Evaluation is gratefully
acknowledged
Essays on financial inclusion in South Africa
No full textPhilosophiae Doctor - PhDSouth Africa is known to be troubled by numerous persistent economic problems of inequality,
poverty and high unemployment. The country is simultaneously praised for a well-developed
financial sector that provides a sophisticated array of financial products. Financial inclusion
plays an important role to eradicate poverty and boost economic prosperity, yet financial
inclusion is an under-researched topic in South Africa. With the growing recognition of the
role financial inclusion plays on the economy, considerable increase in empirical work that
seeks to examine its relationship with economic development has also been seen. A rather
abandoned area is the macroeconomic relations of FI, particularly due to the fact that, until
recent, there was little to no macroeconomic data on FI. This study adopts a threefold approach
in examining FI in South Africa
The impact of real exchange rate volatility on unemployment in South Africa : (Garch Model)
Get PDFMCom (Economics), North-West University, Mafikeng Campus, 2014How macroeconomic models are relevant when pursuing the understanding of exchange rate has been doubted by a large portion of research since the beginning of the 1980 s. This dissertation investigates the impact of the real exchange rate volatility on unemployment in South Africa. Since the two variables are linked with the changes in output and price levels through the production function, this dissertation also covers theories that link the subjects with macroeconomic variables that cannot be ignored when analysing unemployment and exchange rates, such as economic growth, inflation, terms of trade and government expenditure. By so doing the study employs econometric instruments in measuring the relationship between the variables at hand. The Ordinary Least Square (OLS) technique will be used to get the model s
numerical estimates. Argumented Dicky-Fuller stationarity test will be adopted for unit root testing and the Johansen Causality test will be used to test for the direction of causality between the variables. The vector error correction model is employed to examine the existence of a relationship amongst the variables. Finally the study incorporates the GARCH model to test volatility between unemployment and real exchange rate as well as the relationship between the variables. This study is intended to contribute to the growing body of research about South Africa s past experience with the problem of exchange rate volatility. The outcome may provide guidelines and lessons for South Africa. The GARCH model test results indicate that unemployment is insignificant, as such non-volatile. It further suggests that there is an inverse relationship between unemployment and Real Exchange Rate. There is a significant positive relationship between GDP and unemployment. The economic theory however does not agree with these findings because an increase in GDP is expected to decrease unemployment. There is however a negative and significant relationship
between unemployment and export and this happens to be theoretically correct. The study found a negative and statistically significant relationship between CPI and unemployment. These finding agree with the literature of Philips (1958) which means an increase in the level of export is associated with a fall in unemployment.Master
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