Santoso, Danang Budi2016-11-022016-11-022016https://hdl.handle.net/10182/7552Microfinance enables rural households to accumulate assets, smooth consumption in time of economic shocks, reduce the vulnerability due to illness, drought and crop failures, and better education, health and housing for the borrower’s household. In addition, access to finance may contribute to an improvement in the social and economic position of women participation in family decisions making. Microfinance may have positive spill-over effects such that its impact surpasses the economic and social improvement of the borrower. However, there is still concern whether microfinance performance and outreach eminently reaches the poor household. This study aims to investigate the credit accessibility and significant characteristics of rural households who are users of microcredit loans versus non-users of microcredit loans. The study also surveys the welfare impact of microfinance on rural households in Indonesia. The study administered a structured questionnaire to 605 rural households in Bantul District, Yogyakarta Province in Indonesia. Binary Logistic regression is used to investigate credit accessibility of the surveyed respondents. The results reveal that age of borrowers, household income, interest rates, and loan duration are key determinants affecting credit accessibility in the surveyed area. Similarly, binary logistic regression is used to investigate characteristics of the surveyed respondents, based upon whether they used or did not use microcredit. The empirical results suggest that age, marital status and education attainment siginificantly affect characterics of clients and non-clients of microfinance. The multinomial logit model (MNL) is used to assess the welfare impacts of microcredit in term of households income, monthly expenditure and total assets of borrowers. In term of the borrowers income, the MNL shows that age of borrowers, monthly expenditure and occupation are significant factors influencing the increase in income of the borrowers after they have accessed microcredit. In term of borrower’s total assets, the MNL model reveals that more highly educated borrowers are more likely to increase their total assets after accessing microcredit. The MNL model also reveals that only expenditure per month of borrowers has a positive correlation with the increase of welfare impacts of the clients’ expenditures.enmicrofinancepovertyIndonesialogit modelmultinomial logitmicrocreditrural householdsThesisANZSRC::140202 Economic Development and GrowthQ112926418https://creativecommons.org/licenses/by-sa/4.0/Attribution-ShareAlike 4.0 International