| Pub. Date | : Jul, 2020 |
|---|---|
| Product Name | : The IUP Journal of Accounting Research and Audit Practices |
| Product Type | : Article |
| Product Code | : IJARAP20720 |
| Author Name | : Sunil Puliyakot |
| Availability | : YES |
| Subject/Domain | : Finance |
| Download Format | : PDF Format |
| No. of Pages | : 27 |
Borrower over-indebtedness is considered to be a serious risk faced by the microfinance industry globally (CSFI, 2012). The purpose of this paper is to examine whether microfinance participation causes over-indebtedness. Over-indebtedness is identified using the World Bank (WB) estimated poverty line of $1.90 per day. The study uses quantitative methodology using survey design covering 210 borrowing households located in two districts in the state of Tamil Nadu in southern India. It is observed that about 29% of the sample respondents are over-indebted. The results of binomial logistic regression show that microfinance participation does not cause over-indebtedness, and at less than 10% significance level, it brings down the odds of a borrowing household being over-indebted. The key drivers of over-indebtedness are non-MFI borrowing and low household income. The study points to the need to implement income generation schemes before credit distribution schemes as instruments of social policy. From a borrower protection point of view, it also points to the need for regulating informal credit sources.
Experiments of lending to the poor without collateral through unique set of mechanisms like group lending, lending to women borrowers, frequent repayment schedules, etc., commonly characterized as microfinance, had resulted in encouraging outcomes towards the end of the last century (Pitt and Khandker, 1998; and D' Espallier et al., 2011). Consequently, the industry witnessed rapid growth globally since the turn of the century, aided by favorable policy and institutional environment. By the end of the year 2013, the total number of borrowers catered to by Microfinance Institutions (MFIs) grew to approximately 211 million, out of which 114 million were living in extreme poverty (Reed, 2015). This reported growth is amply aided by the ability of the unique mechanisms of microfinance to solve information asymmetry problems between the lender and the borrower without the help of collateral (Besley and Coate, 1995; Ghatak and Guinnane, 1999; and Ghatak, 2000). However, alongside its popularity, fissures also have started appearing, of late, on the consensus of the beneficial effects of microfinance (Roodman and Morduch, 2014; and Banerjee et al., 2015).