Dynamic Analysis of Determinants of Financial Inclusion in Tanzania: Binary Logistic Model

Abstract

Financial inclusion is an important instrument in poverty alleviation and the promotion of a country’s financial prosperity and there is a consensus that financial inclusion is the key driver for economic development. However, few studies have focused on drivers of financial inclusion for developing countries such as Tanzania. This motivated this study, to investigate the potential determinants that influence financial inclusion in Tanzania by using the Dar es Salaam region as a case study. A survey method was used to collect data from a sample of 384 respondents and then the binary Logistic regression model was used to analyze the data through SPSS. The results revealed that income, age, education, and gender are the main drivers of financial inclusion. The level of income, age, and education level are found to have a positive and significant impact on financial inclusion.  Based on the findings the study recommends that the best financial inclusion strategies and policies have to be built by policymakers around these identified drivers to improve the welfare of society through the improvement of financial inclusion in the country.

Keywords:       Binary logistic regression, Drivers of financial inclusion, Financial Services, Financial inclusion