A count model of financial inclusion in Ghana: evidence from living standards surveys
Keywords:
Financial inclusion, Count models, Generalised Poisson model, GhanaAbstract
PurposeThis paper aims to estimate the determinants of the intensity of use of financial inclusion by households in Ghana.
Design/methodology/approachDue to the reality of a household using one or more financial products or services, this study uses the generalised Poisson model applied to GLSS6 and GLSS7 data collected in 2012/2013 and 2016/2017 respectively, to estimate the determinants of the intensity of use of financial inclusion. To deepen the analysis, a multinomial probit model is also applied.
FindingsResults show that infrastructural variables such as roads, public transport and banks stimulate the intensity of financial inclusion. In addition, agricultural development characteristics such as markets and cooperatives are essential for the intensity of inclusion.
Research limitations/implicationsThere is a need to incorporate how many services or depth of services that people use as part of the conceptualisation of financial inclusion, as this can provide more policy-relevant evidence to enhance priority setting in financial inclusion policies. Also, micro-level financial inclusion studies in agrarian economies should consider exploring agricultural development and infrastructure variables in the modelling framework. As lead to further studies, count models of financial inclusion should consider exploring cross-country analysis, the use of panel data, or other methodological approaches to provide more robust evidence.
Originality/valuePrevious studies have not modelled financial inclusion based on a count model as a means of measuring intensity though conceptualisations highlight the fact that people use varied financial products or services. Following from this angle, to the best of the authors’ knowledge, this study provides the first attempt at analysing the underlying determinants of the number of financial products or services used by households.
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