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on Financial Literacy and Education |
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Issue of 2022‒09‒05
three papers chosen by Viviana Di Giovinazzo Università degli Studi di Milano-Bicocca |
| By: | Nyanzu, Frederick |
| Keywords: | Food Consumption/Nutrition/Food Safety, International Development, Agricultural Finance |
| Date: | 2022–08 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea22:322160&r= |
| By: | Miriam Bruhn; Gabriel Garber; Sergio Koyama; Bilal Zia |
| Abstract: | In 2011, the impact of a comprehensive financial education program was studied through a randomized controlled trial with 892 high schools in six Brazilian states. Using administrative data, this paper follows 16,000 students for the next nine years. The short-term findings were that the treatment students used expensive credit and were behind on payments. By contrast, in the long-term treatment, students were less likely to borrow from expensive sources and to have loans with late payments than control students. Treatment students were also more likely to own microenterprises and less likely to be formally employed than control students. |
| Date: | 2022–07 |
| URL: | http://d.repec.org/n?u=RePEc:bcb:wpaper:563&r= |
| By: | Christian Kurniawan; Xiyu Deng; Adhiraj Chakraborty; Assane Gueye; Niangjun Chen; Yorie Nakahira |
| Abstract: | Microfinance in developing areas such as Africa has been proven to improve the local economy significantly. However, many applicants in developing areas cannot provide adequate information required by the financial institution to make a lending decision. As a result, it is challenging for microfinance institutions to assign credit properly based on conventional policies. In this paper, we formulate the decision-making of microfinance into a rigorous optimization-based framework involving learning and control. We propose an algorithm to explore and learn the optimal policy to approve or reject applicants. We provide the conditions under which the algorithms are guaranteed to converge to an optimal one. The proposed algorithm can naturally deal with missing information and systematically tradeoff multiple objectives such as profit maximization, financial inclusion, social benefits, and economic development. Through extensive simulation of both real and synthetic microfinance datasets, we showed our proposed algorithm is superior to existing benchmarks. To the best of our knowledge, this paper is the first to make a connection between microfinance and control and use control-theoretic tools to optimize the policy with a provable guarantee. |
| Date: | 2022–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2207.12631&r= |