Browsing by Subject "Logit Regression Model"

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    Unlocking public and private finance for financial inclusion for individuals at the bottom of the pyramid in Mbare, Zimbabwe
    (2024) Horonga, Rutendo Fortunate; Mthanti, Thanti; Zolfaghar, Badri
    This study aimed to find the barriers faced by the poor in accessing finance, with a specific emphasis on Mbare, a small but bustling township in Zimbabwe known for its lively small scale businesses and markets. Recognizing the significant value of financial inclusion in addressing the large funding deficit was necessary to accomplish the goals of the 2030 Agenda. The research sought to delve into the realities of those living on less than $2.15 per day—a demographic that significantly contributed to this gap. We employed the logit regression method to quantify the extent of financial inclusion and understand the interplay of various factors influencing it. These factors included financial education, the availability of affordable financial services, branchless banking, women empowerment, the perceived role of different sectors in financial inclusion, the experience of the community with collaborative programs, and their awareness of private sector innovations. For data collection, 395 closed-ended questionnaires were distributed within the Mbare community. Out of these, 305 questionnaires were returned and subsequently analysed. The results of this research were pivotal in shedding light on the specific challenges and obstacles that the BOP population in Mbare faced in accessing financial services. The insights gained from this study inform and guide policymakers, financial institutions, Non-Governmental Organizations (NGOs), and academic literature in formulating and implementing strategies that effectively address these barriers and promote financial inclusion. This research represents a step towards understanding and enhancing financial access to the poor in developing countries, thereby contributing to broader efforts aimed at sustainable economic development and poverty alleviation.