Abstract
This study has employed Bayesian Model Averaging (BMA) to identify the most suitable model for assessing the eligibility of Vietnamese coffee farmers for bank loans, effectively avoiding overfitting and ensuring that only the most crucial variables were considered in the analysis. Findings from the study indicate that factors such as ethnicity, labor, yield, land ownership, and willingness to participate (WTP) in coffee insurance significantly influenced the farmers' eligibility for bank loans. Moreover, the study suggests that banks and insurance companies should also take into account additional factors, such as socio-economic context, household size and composition, land ownership, and risk-sharing programs, to enhance access to credit. With this valuable information, banks can forge partnerships with insurance companies to craft highly effective loan programs and insurance products tailored to Vietnamese farmers' unique needs. The simplicity, practicality, and strong predictive ability of the model chosen by BMA make it a valuable tool for guiding policy decisions.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: Journal of Eastern European and Central Asian Research (JEECAR)
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.