Determining and forecasting financial inclusion in Northern Ghana using discriminant analysis

Determining and forecasting financial inclusion in Northern Ghana using discriminant analysis

Issahaku Yakubu, Romanus Dinye, Daniel Buor, Wahab A Iddrisu

Poverty and income inequality remain a serious challenge in Northern Ghana. Given the causal link between financial inclusion and poverty reduction, this paper aims at estimating a discriminant function model to analyze the determinants of financial inclusion in Northern Ghana. The study is mainly based on primary data elicited through survey questionnaires. Even though the minimum sample size was determined to be 385 households, a total of 400 households were selected systematically, out of which 395 households returned their questionnaires for analysis. The estimated discriminant function model was found to be significant at the 1% level of significance. It was also found that, the most significant determinants of financial inclusion in Northern Ghana (in order of importance) are “Age”,“Cost”,“Capability”,“Literacy”,“Distance”, and “Employment”. Overall, 72.4% of the cases were correctly classified by the estimated model. This paper therefore concludes that there is the need for Government and donors to make coordinated efforts towards addressing these determinants so as to broaden financial inclusion, thereby contributing to poverty reduction and lower income inequalities in the area.

2017

https://scholar.google.com/citations?view_op=view_citation&hl=en&user=ECTxVnYAAAAJ&citation_for_view=ECTxVnYAAAAJ:9ZlFYXVOiuMC

English