Research in the field of financial literacy has found that black people and other minority groups, globally, underperform in financial literacy assessments, in comparison to their white counterparts. Multiple factors have been identified in literature, which try to explain the distribution of financial literacy results across demographic groups. However, none of these factors fully explain the disparity. Language has been identified as a potential factor, yet no studies have specifically explored this. A common characteristic among the underperforming group is that financial literacy assessments typically are not conducted in the participants' primary language. This paper aims to explore the impact of the language of assessment by testing whether assessing individuals in their primary language would improve their financial literacy scores. A quantitative research methodology was applied to surveys, which were disseminated in both English and isiXhosa (an African language). The survey performed is in line with existing financial literacy assessment however this study is made unique by controlling for language, to isolate its impact on the results. Statistical analysis of 240 respondents found that language was not the issue. Instead, in line with the findings of existing literature, self-efficacy and educational background are significant in determining financial literacy. These findings are key to financial literacy research and will help in the creation of financial literacy interventions. While there are no retrospective interventions for educational background, self-efficacy can be improved through targeted financial literacy intervention programmes designed to bridge the gap in financial literacy across racial groups.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uct/oai:localhost:11427/37628 |
| Date | 29 March 2023 |
| Creators | Mathebula, Woxy |
| Contributors | Willows, Gizelle |
| Publisher | Faculty of Commerce, College of Accounting |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Master Thesis, Masters, MCom |
| Format | application/pdf |
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