Abstract/Summary

Microfinance research concerns addressed in this thesis relate to: the associations between the individualcharacteristics of borrowers and the probabilities of being in delinquent or default; the determinants for the financial awarenessof interest repayment; and the applicationand comparisonof modern missing data techniques (Multiple Imputation, MaximumLikelihood Estimation, and Predictive Mean Matching) with incomplete loan book data.The thesis emphasises credit scoring issues that affect repayment performanceandre-volves around threeempirical chapters thatseek to address the above research concerns. Survey and loan book data from individualsin 51 MFIsacross 27developingcountries. The data were compiled by the MFIsand collected by Micro Finanza Rating. Varied micro-econo-metric techniques (ordinary least squares, Logit regression, Tobit regression, Two-Part model, Double-Hurdle model, Box-Cox transformation, and three missing data imputation methods: Multiple Imputation, Maximum Likelihood Estimation, andPredictive Mean Matching) are used depending on the hypotheses being consideredin eachchapter. The main findings are: engaging in agriculture is related to a lower probability of default that measured by the amount of arrear in general; besides, the association between agriculture and the length of delayed repayment is insignificant; previous access to micro-finance haspositive association with the financial awareness of the clients who lived in urban areas; in addition, previous access to saving service has positive effect on the clients with at least primary education; when the missing microfinance data is semi-continuous, PMM outperformsMI and ML in most simulations; for binary or ordinal categorical data, PMM performance surpass MI and ML only when the sample sizes of data are large, the missing rates are low, and the missing mechanism is MAR. The thesis suggests the following recommendationboth for management of MFIs and government: we need tomakefinancial services for poor farm households and farm-related business more attractive to the MFIs; financial awareness can be improved by access to microfinance services, hence extra learning programmesmay be unnecessary; Two-Part Model shouldbe applied to credit scoring;and PMM imputation is the best technique to be applied to deal with the missing data issues and improve data quality inmicrofinance.