INFLUENCE OF SOCIAL NETWORKS IN ACCESSING INFORMAL CREDIT AND RESULTING EFFECTS ON AGROPASTORAL HOUSEHOLD’S WELFARE IN WESTPOKOT COUNTY, KENYA

Abstract

Over the years, rural agropastoral households have continuously been financially excluded. Formal financial institutions have locked them out of accessing credit due to the high risk involved and lack of collateral to secure loans. As a result, social networks have often been used by these households in their attempt to source credit to finance their agricultural activities, smooth consumption and cope with risks. Little is known about how these lending networks form, operate, influence credit access and their effects on household welfare in Kenya. This study aimed to understand the antecedents of networking, how social networks influence the access to informal credit and improve welfare in Pokot South sub-county. It was guided by four objectives: To characterize the social networks among agropastoral households, to determine the factors that influence household participation in lending networks in Pokot-South sub-county, to determine the factors that influence the access to informal credit among households and to investigate the effects of informal credit on household welfare in Pokot South sub-county. A multi-stage sampling technique was used to select 198 households and primary cross-sectional data was collected using a pre-tested semi-structured questionnaire. In the analysis, social network analysis (SNA) methodology was used to illustrate the network structure revealed by the households. Exponential random graph model (ERGM) was used to determine drivers of networking among households. A multiple linear regression model was used to analyse the determinants of access to informal credit and an Endogenous Switching Regression (ESR) Model used to investigate the effects of informal credit on household welfare. Data was analysed using both STATA and R statistical software. Results revealed that the lending network was decentralized, had above average reciprocity and highly resilient. Networking among households was influenced by reciprocity, income, sex of the household head, primary occupation and age of household head. Informal credit access was determined by the number of adults in the household, occupation, farm size, livestock ownership, income and purpose of credit. In counterfactual cases, households that had higher credit access increased their likelihood of having higher welfare by 24.61% as compared to those with low informal credit access. In conclusion, informal credit obtained through social networks contributed towards improved agropastoral household welfare. This study recommends promotion of building social capital, enhancing household wealth and income diversification.