Haruna Issahaku, Munira Alhassan Muhammed, Benjamin Musah Abu
{"title":"加纳普惠金融的计数模型:来自生活水平调查的证据","authors":"Haruna Issahaku, Munira Alhassan Muhammed, Benjamin Musah Abu","doi":"10.1108/jefas-10-2021-0204","DOIUrl":null,"url":null,"abstract":"Purpose This paper aims to estimate the determinants of the intensity of use of financial inclusion by households in Ghana. Design/methodology/approach Due 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. Findings Results 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/implications There 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/value Previous 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.","PeriodicalId":53491,"journal":{"name":"Journal of Economics, Finance and Administrative Science","volume":"84 6","pages":"0"},"PeriodicalIF":2.3000,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A count model of financial inclusion in Ghana: evidence from living standards surveys\",\"authors\":\"Haruna Issahaku, Munira Alhassan Muhammed, Benjamin Musah Abu\",\"doi\":\"10.1108/jefas-10-2021-0204\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Purpose This paper aims to estimate the determinants of the intensity of use of financial inclusion by households in Ghana. Design/methodology/approach Due 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. Findings Results 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/implications There 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/value Previous 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.\",\"PeriodicalId\":53491,\"journal\":{\"name\":\"Journal of Economics, Finance and Administrative Science\",\"volume\":\"84 6\",\"pages\":\"0\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2023-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Economics, Finance and Administrative Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/jefas-10-2021-0204\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Economics, Finance and Administrative Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/jefas-10-2021-0204","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
A count model of financial inclusion in Ghana: evidence from living standards surveys
Purpose This paper aims to estimate the determinants of the intensity of use of financial inclusion by households in Ghana. Design/methodology/approach Due 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. Findings Results 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/implications There 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/value Previous 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.
期刊介绍:
The Universidad ESAN, with more than 50 years of experience in the higher education field and post graduate studies, desires to contribute to the academic community with the most outstanding pieces of research. We gratefully welcome suggestions and contributions from business areas such as operations, supply chain, economics, finance and administration. We publish twice a year, six articles for each issue.