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    Factors affecting the performance of the pension sector in Uganda

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    Ssempungu-CoBAMS-Bachelors.pdf (1.099Mb)
    Date
    2021-08
    Author
    Ssempungu, JR Charles
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    Abstract
    Recently Uganda’s pension system has not been performing to world standard and this is as a result of some underlying issues embedded in the pension regime. Additionally, the liberalization bill was tabled before parliament in 2011 with objectives seen as solution to the prevailing issues. Its main objective was to remove monopoly of a single retirement benefits scheme over mandatory contributions and others including providing for fair competition among licensed retirement benefits schemes for mandatory contributions; providing for mandatory contributions and benefits; consolidating and reform the law relating to retirement benefits and others. However, it has not yet been passed ever since. For its effective implementation in the future when it is passed, certain currently and factors have to be resolved so that the required results are achieved. And on the other hand in case it is not passed, these underlying issues and factors have to be combated for the betterment of the industry. This propelled the researcher to carry out research concerning these factors so that I can deeply understand their extent towards the performance of the pension sector and relay the information. The research objectives where to analyze the extent to which social-demographic which included age, gender, level of education, and economic factors such as density of contributions, fund size, level of fund governance, inflation, costs and coverage and also knowledge affect the performance of the pension sector. Primary data was collected from the respondents using questionnaires. Respondents were asked on their opinions regarding Uganda’s pension sector performance, which also was used as the dependent variable while using the binary logistic regression model and the social-demographic factors, economic factors and knowledge used as the independent variables while running the model in Stata
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    http://hdl.handle.net/20.500.12281/9963
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