Data for: Inclusive Green Finance for Sustainable Agriculture in Rural Namibia_ Transforming Rural Livelihoods Through Climate-Smart Financial Solutions

This dataset originates from a survey conducted among farmers in Namibia as part of a study on inclusive green finance and sustainable agricultural practices. Predesigned questionnaires were developed by the consultant and the Bank, and approved prior to data collection. The survey employed both descriptive and exploratory research designs to answer questions such as who, what, and how. This dual approach enabled the capture of both qualitative and quantitative data, thereby enhancing the reliability, credibility, and validity of the findings. The survey results form the basis of the study, which examines the role of inclusive green finance in promoting sustainable agriculture and the impact of climate change on farming practices and financial service accessibility, with a focus on gender differences. Additionally, the study explores how green financing mechanisms such as grants, low-interest loans, and investment opportunities can support rural communities in transitioning to more resilient agricultural systems. The dataset consists of responses from 320 farmers, including 24 commercial farmers and 296 small-scale farmers. The survey was conducted through face-to-face interviews by enumerators from Business Intelligence Africa (BIA) between November and December 2024. Data collection lasted about twenty days, covering selected regions based on the prevalence of farming, agricultural activities, financial exclusion, and logistical constraints. To ensure quality, 10% back checks were carried out via follow-up phone calls to confirm interviews and validate responses; no questionnaires were withdrawn, though some were returned for clarification. In addition to farmer responses, Financial Service Providers were also interviewed to gather their perspectives on the challenges they face in supporting the agricultural sector, particularly in managing the effects of climate change. The data collection process was followed by rigorous cleaning, back-checking, and analysis to ensure accuracy and consistency.