Open AccessRisks to credit access in a developing economy
Author(s) -
Uduakobong Inyang
Publication year - 2022
Publication title -
international journal of research in business and social science
Language(s) - English
Resource type - Journals
ISSN - 2147-4478
DOI - 10.20525/ijrbs.v11i2.1628
Subject(s) - developing country , credit history , bond market , binomial regression , business , information asymmetry , informal sector , household income , logistic regression , estimation , economics , demographic economics , finance , economic growth , medicine , management , archaeology , history
Governments in developing economies are continuously seeking ways to increase the number of people that have access to formal financial services. However, literature on why households in developing economies are excluded from the formal credit sector is scarce. Thus, this study examines the link between household characteristics and the choice of credit provider using unique household-level primary data from the Niger Delta region. A binomial logistic regression model based on relevant household characteristics is developed for estimation. The results show that the number of dependents and income of a household, as well as education level and age of household head, is relevant in understanding the choice of the credit provider. Strikingly, the finding that the probability of borrowing from the informal sector increases with household distance from a formal lender at a decreasing rate suggests the significance of cost associated with traveling to the nearest bank on the choice of a lender and the presence of information asymmetry in the credit market of the region. Overall, the study raises important implications to inform credit market policies and practices in the region.