*Names in bold indicate Presenter
Because all households are poor in our sample, it increases the chances that they have borrowed from microfinance institutions. Thus, while the specific lender is unknown, it is known whether a borrower takes out a loan through formal banking system (private banks, state banks, non-profit organizations, cooperatives and associations) or informal banking system (friends, relatives and moneylenders). Relying on microfinance literature, we discuss several channels through which microcredit may positively affect children’s schooling:
- income effect (investment in productive activities increases income and contributes to more schooling),
- risk-management effect (credit helps to keep children in school during economic shocks)
- gender effect (microfinance often targets women who are believed to invest more in children’s human capital),
- information effect (information and training sessions organized by microfinance organizations change perceptions about schooling),
- deposits effect (deposits are a risk-management strategy and also have behavioral implications, such as developing self-control, inter-temporal patience, which positively influence schooling),
- social network effect (borrower’s interactions with other borrowers and loan officers influence borrower’s decisions to invest in schooling).
Borrowing may also have negative effects or absence of effects on schooling through the following mechanisms:
- child-labor demand effect (productive activities require parents to put their children to work in productive activities or household work),
- waiting/delays effect (as parents spend time on managing loans, children substitute them in household work while parents are gone),
- default effect
- loan amount effect In this study, we focus on three schooling outcomes: school attendance, highest grade attempted and schooling gap. Additionally, we split borrowing into credit from the formal banking system and credit from the informal banking system. Schooling outcomes are analyzed for girls and boys from non-borrowing households, households with a female borrower and households with a male borrower.
Using regression analysis, preliminary findings indicate that girls from non-borrowing households compared to girls from households with a female borrower, and boys from non-borrowing households compared to boys from households with a male borrower tend to have better schooling outcomes. Additionally, girls from households with a female borrower have on average lower schooling outcomes compared to girls from households with a male borrower. These findings provide support for the child-labor demand effect driven by substitutability/complementarity of time and skills between borrowers and children of the same gender.